F1IS1_15 Applied Statistics

Faculty of Pharmacy
Autumn 2022
Extent and Intensity
2/2/0. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
doc. RNDr. Bc. Jiří Pazourek, Ph.D. (lecturer)
PharmDr. Pavlína Marvanová, Ph.D. (seminar tutor)
doc. RNDr. Bc. Jiří Pazourek, Ph.D. (seminar tutor)
Mgr. Sylvie Pavloková, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Bc. Jiří Pazourek, Ph.D.
Department of Chemical Drugs – Departments – Faculty of Pharmacy
Supplier department: Department of Chemical Drugs – Departments – Faculty of Pharmacy
Timetable
Tue 12:35–14:15 44-056
  • Timetable of Seminar Groups:
F1IS1_15/01: Tue 14:30–16:10 44-016, J. Pazourek
F1IS1_15/02: Tue 16:25–18:05 44-016, S. Pavloková
Prerequisites (in Czech)
FAKULTA(FaF) || OBOR(MUSFaF)
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.

The capacity limit for the course is 50 student(s).
Current registration and enrolment status: enrolled: 26/50, only registered: 0/50
fields of study / plans the course is directly associated with
Course objectives
Statistical evaluation of results is essential part of all experimental scientific branches. The content of this subject is basic statistics for a graduate student of the study program "Pharmacy". Lessons concern mainly descriptive statistics, partially also the probability calculus and mathematical statistics with a direct relationship to real scientific tasks of experimental work (evaluation of experimental data, hypotheses formulation and testing). Practical exercises include introduction to PC´s hardware and software and utilization of spreadsheet programs (MS Excel, Gnumeric).
Learning outcomes
After completing the course, the student will be able to: - use a spreadsheet calculators (MS Excel) - perform basic descriptive statistics - select and perform basic statistical tests for one, two or more samples
Syllabus
  • Content of the lecture Stochastic world. The effects of random on our data - the goal of statistics. Population and samples in statistics. Random experiment - random phenomenon - random variables, types of statistical variables. Observation and data collection. Frequency of random occurrence. Relative frequency of a random variable and probability. Frequency polygons and histograms. Compilation of tables from observations. Graphic presentation of experimental data: histograms, bar graphs, pie charts, xy-graphs (scatter graphs). Quantiles, box-and-whiskers plot_1. Data processing with spreadsheets: interpolation and extrapolation of functions, numerical integration of digital signal - chromatographic peak, determination of chromatographic peak area. Signal noise filtering. Probability and distribution function = DISTRIBUTION. Probability functions. Binomial distribution. Other types of distributions: uniform, Poisson distribution, Student's t-distribution. Gaussian normal distribution - properties. Empirical and theoretical distribution curve. chi2-distribution. Goodness-of-Fit Test (Pearson's Chi2-test, Goodness-of-Fit Test). Normality tests: Lilliefors (Kolmogorov-Smirnov) normality test; Q-Q chart. Descriptive statistics, descriptive characteristics of statistical samples. Estimation of basic set parameters - mean values ​​and measures of variability; median, mode. Mean and standard deviation. Rounding. SEM, Confidence interval. Elimination of outliers - outliers. Quartiles, box-and-whiskers plot_2 - inner fence method (Tukey) Grubbs test. Dean-Dixon Q-test. Inferential statistics - basics of statistical tests = distribution and hypotheses: HYPOTHESES in statistics, error of the first and second kind. Which test to use? 1-sample, paired, 2-sample tests. One-sided and two-sided test. Two-sample parametric tests for equality: Sign test. Wilcoxon test. Mann-Whitney U-test. Student's t-test. + Fisher's variance equality test. Multi-sample parametric tests: One-factor ANOVA - analysis of variances of multiple samples. Kruskal-Wallis test for multiple samples. Evaluation of the dependence of two quantitative features. Pivot Tables. Pearson's Chi-independence test. Four-field tables (2x2) - Fisher's exact test. Correlation and regression. Spearman's coefficient of order correlation. Linear regression dependence - Pearson correlation coefficient. Residuals. Regression ANOVA. Testing the significance of the regression dependence section. Quantitative analysis calculations: calibration curve method. Factors significantly influencing the experiment - The plan of experiments and its evaluation. Plackett-Burman experimental plan. Survival analysis. Clinical studies. Tests´ overview. Revision of key knowledge Exercise content: 1. Use of personal computers in scientific work. MS Office. 2. MS Excel spreadsheet. Table editing, basic calculations (formulas), filters. Simple graphs in   Excel + line vs. xy-graph. Analytical signal processing - chromatographic peak. Peak integration numerically. Assignment - numerical integration. 3. Descriptive statistics: processing of measurements using basic characteristics of statistical files - use of the mean value. Quantiles (arithmetic mean, median, mode, quartiles). Box chart. Histogram - Excel / Gnumeric.exe. MS Excel module Data analysis. Assignment - deciles/histogram. 4. descriptive statistics in MS Excel. MS Excel module Data analysis. Mean and standard deviation. Rounding. Elimination of outliers (Grubbs test, Q-test). Internal wall method - modified box graph. Confidence interval for continuous and categorical data. Assignment - confidence interval incl. remoteness test. 5. Inference statistics - H0 and H1. Goodness-of-fit test. Empirical distribution function (EDF). Normality testing: Q-Q graph, Kolmogorov-Smirnov (Lilliefors) test: Gnumeric.exe. Randomness testing - runs test. Assignment - EDF tests. 6. One-sample and two-sample tests. Testing of equality: sign test (paired nonparametric test). Wilcoxon's signed-rank test. Parametric alternatives: F-test (equality of variance), t-test of equality (unpaired and paired). Assignment - MW test. 7. Mann-Whitney U-test. Multiple-sample tests: One-factor ANOVA, Kruskal-Wallis test. Friedman's test. Assignment - ANOVA 8. four-field tables 2x2. (N-1) chi2 test Risk ratio, Fisher's exact test. Correlation analysis: large contingency tables, two-dimensional chi2 test. Assignment - Pivot Table. 9. Spearman's correlation coefficient. Construction of calibration curve by linear regression, regression ANOVA, Assignment - calibration graph, residuals. 10. Linear regression - test of significance of a section (MS Excel, other statistical programs). Assignment - regression with data transformation. 11. Survival analysis: censored data, construction of survival curve, determination of median survival. Revision. 12. Independent work in statistical data processing. Exam (written test)
Literature
    required literature
  • Pavlík, Dušek. Biostatistika. MU Brno, 2012. URL info
    recommended literature
  • Bedáňová, Večerek. Základy statistiky. VFU Brno, 2007. URL info
Teaching methods
Monologic (presentation, lecture, practical classes)
Assessment methods
written examination
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course can also be completed outside the examination period.
Teacher's information
https://moodlinka.ics.muni.cz/course/view.php?id=3507
Condition for passing the exam: absence in max. 1 seminar preparation of an assignment from each seminar Criteria for passing the exam: practical test (PC test) with a score of more than 50%
The course is also listed under the following terms Autumn 2020, Autumn 2021, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2022, recent)
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