FAIS1_15 Applied Statistics

Farmaceutická fakulta
podzim 2021
Rozsah
2/2/0. 5 kr. Doporučované ukončení: zk. Jiná možná ukončení: z.
Vyučující
doc. RNDr. Bc. Jiří Pazourek, Ph.D. (přednášející)
doc. RNDr. Bc. Jiří Pazourek, Ph.D. (cvičící)
Garance
doc. RNDr. Bc. Jiří Pazourek, Ph.D.
Ústav chemických léčiv – Ústavy – Farmaceutická fakulta
Rozvrh
Po 12:25–14:05 44-037
  • Rozvrh seminárních/paralelních skupin:
FAIS1_15/01: Po 14:20–16:00 44-016, J. Pazourek
Předpoklady
FAKULTA(FaF) || OBOR(MUSFaF)
Omezení zápisu do předmětu
Předmět je určen pouze studentům mateřských oborů.

Předmět si smí zapsat nejvýše 20 stud.
Momentální stav registrace a zápisu: zapsáno: 2/20, pouze zareg.: 0/20
Mateřské obory/plány
Cíle předmětu
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).
Výstupy z učení
After completing the course, the student will be able to: - use a computer to obtain information from scientific information sources (search) and his/her work - use a spreadsheet calculators (MS Excel) - perform basic descriptive statistics - select and perform basic statistical tests for one, two or more samples
Osnova
  • Content of Lectures: Our stochastic world. The impact of probability onto our (experimental) data. The meaning of statistics. The roll of dice – random circumstances. The random experiment I: relative frequencies of observations and probability. Distribution function – normal distribution (Gaussian), probability density function. Population and samples. Descriptive statistics. Population parameters and their estimations. Student´s distribution, the central limit theorem. Means (average, median, modus…), measures of variability: standard deviation, variance. The random experiment II: Construction of tables from experimental data, type of variables on scales – nominal, ordinal, interval and ratio scales. Graphs from experimental data: histograms vs. bar graphs, frequency polygons, XY-charts, quantiles, Box-and-whiskers plot I Tests for outliers removal – Box-and-whiskers plot II: outliers, Grubbs test for outliers, significant digits – rounding off. Confidence interval. Hypotheses and test. Statistical tests: Alpha and beta errors. Null and alternative hypothesis, critical values/p-values, level of significance alpha. The empirical and the expected distribution – chi-square (Goodness-of-fit) test. Parametric and non-parametric tests.F-test, two sample t-test for equality of means Non-parametric alternatives of one- and two-sample tests Relationship between two quantitative variables: Pearson´s chi2-test of independency. Correlation and regression, Spearman´s rank correlation coefficient. Linear regression – Pearson´s correlation coefficient. Test of the intercept significance. Contents of practical lessons: Applications of PC for pharmacy study. Internet information sources. Scientific databases on-line; info-search with logical operators. ISI Web of Knowledge, Science Direct- reference search on VFU. Practical searching exercise according to key words How to work with MS Excel. Editing a spreadsheet, basic calculations (formulas), graphical presentation of data. Analytical signal evaluation - the chromatographic peak. Numerical integration. Evaluation of experimental data by basic descriptive statistics (arithmetic mean, median, modus, quantiles). Calculation: basic statistical characteristics of a data set. Graphical presentation of experimental data: polygon and histogram of frequencies, bar chart, pie chart, xy-graph. Quantiles - box-and-whiskers plots construction. Gnumeric.exe Experimental data evaluation (random errors). Average. Standard deviation. Rounding off. Confidence interval. Data evaluations (outliers) - outliers removal (Grubbs test). Outliers: the method of inner boundaries - an adopted box-and-whiskers plot. Null hypotheses. Normality tests: Lilliefors test (Gnumeric.exe). Modules in MS Excel Data analysis: descriptive statistics, two-sample F-test (comparison of variances), t-test (two-sample test with unequal variances). ANOVA Non-parametric statistical alternatives: sign test, Wilcoxon rank sum test (Mann-Whitney U-test). Kruskal-Wallis test Fourfold tables, Fisher exact test. Contingency tables Spearman´s coefficient rho of rank correlation, Person´s r Linear regression - construction. Calibration graph construction by the linear regression, interpretation of the model Linear regression - test of the intercept significance (H0: a=0). Final test. Examination (written)
Literatura
    doporučená literatura
  • Massart. Handbook of Chemometrics and Qualimetrics. Amsterdam, 1997. info
Výukové metody
Monologic (presentation, lecture, practical classes)
Metody hodnocení
written examination
Vyučovací jazyk
Angličtina
Informace učitele
https://is.muni.cz/auth/el/pharm/podzim2020/F1IS1_15/index.qwarp
Criteria for granting credit: taking part in at least 12 seminars during the semester (of 13 possible) elaboration of assignments from each seminar Criteria for taking the examination test: granted credits passing a practical exam (a PC test)
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Předmět je zařazen také v obdobích jaro 2020, podzim 2020, podzim 2022, podzim 2023, podzim 2024.