FAIS1_15 Applied Statistics

Farmaceutická fakulta
podzim 2024
Rozsah
2/2/0. 5 kr. Ukončení: zk.
Vyučováno prezenčně.
Vyučující
doc. RNDr. Bc. Jiří Pazourek, Ph.D. (přednášející), Ing. Klára Odehnalová, Ph.D. (zástupce)
doc. RNDr. Bc. Jiří Pazourek, Ph.D. (cvičící), Ing. Klára Odehnalová, Ph.D. (zástupce)
Garance
doc. RNDr. Bc. Jiří Pazourek, Ph.D.
Ústav chemických léčiv – Ústavy – Farmaceutická fakulta
Předpoklady
FAKULTA ( FaF ) || OBOR ( MUSFaF )
Omezení zápisu do předmětu
Předmět je určen pouze studentům mateřských oborů.

Předmět si smí zapsat nejvýše 25 stud.
Momentální stav registrace a zápisu: zapsáno: 0/25, pouze zareg.: 0/25
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)
Další komentáře
Předmět je dovoleno ukončit i mimo zkouškové období.
Předmět je zařazen také v obdobích jaro 2020, podzim 2020, podzim 2021, podzim 2022, podzim 2023.