Bi5040 Biostatistics - basic course
Faculty of Scienceautumn 2021
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 14 fields of study the course is directly associated with, display
- Course objectives
- The aim of the course is to provide students with basic principles of statistical analysis of biological data from the experimental design, data collection and visualisation to descriptive statistics and statistical hypotheses testing.
- Learning outcomes
- At the end of the course the students are able to:
Define structure of dataset for statistical analysis;
Visualize the data and interpret data visualisation;
Identify correct methods of descriptive statistics;
Formulate hypothesis for statistical testing;
Select the correct statistical tests for hypotheses confirmation/refusal;
Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature;
Assess the applicability of statistical methods on various types of data. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Presentations in Microsoft Teams; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2020
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Wed 17:00–19:50 prace doma
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 14 fields of study the course is directly associated with, display
- Course objectives
- The aim of the course is to provide students with basic principles of statistical analysis of biological data from the experimental design, data collection and visualisation to descriptive statistics and statistical hypotheses testing.
- Learning outcomes
- At the end of the course the students are able to:
Define structure of dataset for statistical analysis;
Visualize the data and interpret data visualisation;
Identify correct methods of descriptive statistics;
Formulate hypothesis for statistical testing;
Select the correct statistical tests for hypotheses confirmation/refusal;
Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature;
Assess the applicability of statistical methods on various types of data. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Presentations in Microsoft Teams; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further comments (probably available only in Czech)
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2019
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 14 fields of study the course is directly associated with, display
- Course objectives
- The aim of the course is to provide students with basic principles of statistical analysis of biological data from the experimental design, data collection and visualisation to descriptive statistics and statistical hypotheses testing.
- Learning outcomes
- At the end of the course the students are able to:
Define structure of dataset for statistical analysis;
Visualize the data and interpret data visualisation;
Identify correct methods of descriptive statistics;
Formulate hypothesis for statistical testing;
Select the correct statistical tests for hypotheses confirmation/refusal;
Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature;
Assess the applicability of statistical methods on various types of data. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2018
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Mon 17. 9. to Fri 14. 12. Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 7 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
Bi5040 Biostatistics - basic course
Faculty of Scienceautumn 2017
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Mon 18. 9. to Fri 15. 12. Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 7 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2016
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Mon 19. 9. to Sun 18. 12. Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 7 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2015
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 7 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2014
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
Mgr. Jan Fikejs (assistant)
Mgr. Ivana Kupčíková, DiS. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 7 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2013
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Mon 16. 9. to Fri 6. 12. Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 7 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and nonparametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Nonparametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask questions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisites and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2012
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D.
Supplier department: RECETOX – Faculty of Science - Timetable
- Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 12 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2011
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D. - Timetable
- Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 12 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2010
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D. - Timetable
- Wed 17:00–19:50 B11/132
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2009
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D. - Timetable
- Wed 17:00–19:50 A,01026
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2008
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Tomáš Pavlík, Ph.D. (seminar tutor) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D. - Timetable
- Wed 17:00–19:50 A,01026
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- Introduction to statistics, testing of hypotheses.
Tables of distribution functions.
Introduction to sampling design.
Distribution of continuous and bivariate variables.
Application of binomial and Poisson distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Measures of similarity in ecology.
Analysis of variance (ANOVA).
Simple linear regression. Linear regression.
Experimental design. Non - parametric ANOVA.
The student will obtain skills in correct statistical analysis of biological data. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2007
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Jan Mužík, Ph.D. (assistant)
RNDr. Eva Gelnarová (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D. - Timetable
- Wed 17:00–19:50 A,01026
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- Introduction to statistics, testing of hypotheses.
Tables of distribution functions.
Introduction to sampling design.
Distribution of continuous and bivariate variables.
Application of binomial and Poisson distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Measures of similarity in ecology.
Analysis of variance (ANOVA).
Simple linear regression. Linear regression.
Experimental design. Non - parametric ANOVA. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
- G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
- HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
- J. Benedík, L. Dušek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2006
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Jan Mužík, Ph.D. (assistant)
RNDr. Eva Gelnarová (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D. - Timetable
- Wed 17:00–19:50 A,01026
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- Introduction to statistics, testing of hypotheses.
Tables of distribution functions.
Introduction to sampling design.
Distribution of continuous and bivariate variables.
Application of binomial and Poisson distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Measures of similarity in ecology.
Analysis of variance (ANOVA).
Simple linear regression. Linear regression.
Experimental design. Non - parametric ANOVA. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
- G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
- HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
- J. Benedík, L. Dušek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2005
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Jan Mužík, Ph.D. (assistant)
RNDr. Eva Gelnarová (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D. - Timetable
- Wed 16:00–19:50 U-aula
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- Introduction to statistics, testing of hypotheses.
Tables of distribution functions.
Introduction to sampling design.
Distribution of continuous and bivariate variables.
Application of binomial and Poisson distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Measures of similarity in ecology.
Analysis of variance (ANOVA).
Simple linear regression. Linear regression.
Experimental design. Non - parametric ANOVA. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
- G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
- HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
- J. Benedík, L. Dušek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- Study Materials
The course is taught annually. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2004
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Jan Mužík, Ph.D. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D. - Timetable
- Wed 16:00–19:50 P0
- Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- Introduction to statistics, testing of hypotheses.
Tables of distribution functions.
Introduction to sampling design.
Distribution of continuous and bivariate variables.
Application of binomial and Poisson distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Measures of similarity in ecology.
Analysis of variance (ANOVA).
Simple linear regression. Linear regression.
Experimental design. Non - parametric ANOVA. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
- G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
- HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
- J. Benedík, L. Dušek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
- Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2003
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Jan Mužík, Ph.D. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D. - Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- Introduction to statistics, testing of hypotheses.
Tables of distribution functions.
Introduction to sampling design.
Distribution of continuous and bivariate variables.
Application of binomial and Poisson distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Measures of similarity in ecology.
Analysis of variance (ANOVA).
Simple linear regression. Linear regression.
Experimental design. Non - parametric ANOVA. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
- G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
- HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
- J. Benedík, L. Dušek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
The course is taught: every week. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2002
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jan Mužík, Ph.D. (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
Department of Botany and Zoology – Biology Section – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D. - Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- Introduction to statistics, testing of hypotheses.
Tables of distribution functions.
Introduction to sampling design.
Distribution of continuous and bivariate variables.
Application of binomial and Poisson distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Measures of similarity in ecology.
Analysis of variance (ANOVA).
Simple linear regression. Linear regression.
Experimental design. Non - parametric ANOVA. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
- G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
- HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
- J. Benedík, L. Dušek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
The course is taught: every week. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2011 - acreditation
The information about the term Autumn 2011 - acreditation is not made public
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D. - Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
The course is taught: every week. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2010 - only for the accreditation
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- RNDr. Jiří Jarkovský, Ph.D. (lecturer)
- Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: RNDr. Jiří Jarkovský, Ph.D. - Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- At the end of the course the students are able to: Define structure of dataset for statistical analysis; Visualize the data and interpret data visualisation; Identify correct methods of descriptive statistics; Formulate hypothesis for statistical testing; Select the correct statistical tests for hypotheses confirmation/refusal; Interpret results of statistical evaluation, both analysis of own data and statistics in scientific literature; Assess the applicability of statistical methods on various types of data.
- Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Petrie, A., Watson, P. (2006) Statistics for Veterinary and Animal Science, Wiley-Blackwell; 2nd ed
- Zar, J.H. (1998) Biostatistical analysis. Prentice Hall, London. 4th ed.
- Sokal, R.R., Rohlf, F.J. (1994) Biometry, W. H. Freeman, 3th ed.
- Teaching methods
- Theoretical lectures supplemented by commented examples; students are encouraged to ask quaetions about discussed topics.
- Assessment methods
- Biostatistics course is finished by written exam aimed on principles, prerequisties and correct selection of methods for solution of practical examples.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
The course is taught: every week. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
Bi5040 Biostatistics - basic course
Faculty of ScienceAutumn 2007 - for the purpose of the accreditation
- Extent and Intensity
- 3/0/0. 3 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
- Teacher(s)
- prof. RNDr. Ladislav Dušek, Ph.D. (lecturer)
RNDr. Jiří Jarkovský, Ph.D. (lecturer)
RNDr. Jan Mužík, Ph.D. (assistant)
RNDr. Eva Gelnarová (assistant) - Guaranteed by
- prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX – Faculty of Science
Contact Person: prof. RNDr. Ladislav Dušek, Ph.D. - Prerequisites
- None - basic course.
- Course Enrolment Limitations
- The course is also offered to the students of the fields other than those the course is directly associated with.
- fields of study / plans the course is directly associated with
- there are 6 fields of study the course is directly associated with, display
- Course objectives
- Introduction to statistics, testing of hypotheses.
Tables of distribution functions.
Introduction to sampling design.
Distribution of continuous and bivariate variables.
Application of binomial and Poisson distribution in biology.
One sample testing.
Two sample testing.
Application of goodness-of-fit test in biology.
Measures of similarity in ecology.
Analysis of variance (ANOVA).
Simple linear regression. Linear regression.
Experimental design. Non - parametric ANOVA. - Syllabus
- Introduction to statistics, testing of hypotheses.
- Tables of distribution functions. Sampling from biological populations, data processing.
- Introduction to sampling design. Continuous, ordinal and nominal data in biology.
- Distribution of continuous and bivariate variables - testing of hypotheses, graphical methods.
- Application of binomial and Poisson distribution in biology.
- One sample testing: sample mean, median, standard deviation, variance, binomial p and Poisson constant.
- Two sample testing. Experimental design - randomized and blocked. Parametric and non - parametric methods.
- Application of goodness-of-fit test in biology, analysis of R x C contingency tables, discrimination of categorical data.
- Measures of similarity in ecology (covariance, correlation coefficients, similarity coefficients).
- Analysis of variance (ANOVA): one-way and two-way model.
- Simple linear regression. Linear regression. Introduction to multivariate linear regression.
- Experimental design: one-way and two-way models; factorial design, randomized blocks. Laboratory and field trials. Nested design of ANOVA in genetics and ecology. Non - parametric ANOVA.
- Literature
- Zar, J.H. (1994) Biostatistical methods. Prentice Hall, London. 2nd ed.
- G. W. Snedecor, W. G. Cochran (1971). Statistical methods. Iowa State University Press.
- HAVRÁNEK, Tomáš. Statistika pro biologické a lékařské vědy. 1. vyd. Praha: Academia, 1993, 476 s. ISBN 8020000801. info
- J. Benedík, L. Dušek (1993) Sbírka příkladů z biostatistiky. Nakladatelství KONVOJ, Brno.
- Language of instruction
- Czech
- Follow-Up Courses
- Further Comments
- The course is taught annually.
The course is taught: every week. - Listed among pre-requisites of other courses
- Bi5180 Quantitative genetics
Bi3060 && Bi5040 || E5540 - Bi7920 Analysis of biological data
Bi5040||Bi5560 - Bi7921 Advanced methods of analysis of biological data
(Bi5040||Bi5560) && Bi7920 - E7490 Advanced non-parametric methods
Bi5040 || Bi5045 - E7528 Analysis of genomic and proteomic data
(Bi5040 || Bi5045 || Bi5046 || E5046) && E8600 && E7527 && Bi4010 && E0034
- Bi5180 Quantitative genetics
- Teacher's information
- http://www.cba.muni.cz/vyuka/
- Enrolment Statistics (recent)