FAIS1_15 Applied Statistics

Faculty of Pharmacy
Autumn 2021
Extent and Intensity
2/2/0. 5 credit(s). Recommended Type of Completion: zk (examination). Other types of completion: z (credit).
Teacher(s)
doc. RNDr. Bc. Jiří Pazourek, Ph.D. (lecturer)
doc. RNDr. Bc. Jiří Pazourek, Ph.D. (seminar tutor)
Guaranteed by
doc. RNDr. Bc. Jiří Pazourek, Ph.D.
Department of Chemical Drugs – Departments – Faculty of Pharmacy
Timetable
Mon 12:25–14:05 44-037
  • Timetable of Seminar Groups:
FAIS1_15/01: Mon 14:20–16:00 44-016, J. Pazourek
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 20 student(s).
Current registration and enrolment status: enrolled: 2/20, only registered: 0/20
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 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
Syllabus
  • 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)
Literature
    recommended literature
  • Massart. Handbook of Chemometrics and Qualimetrics. Amsterdam, 1997. info
Teaching methods
Monologic (presentation, lecture, practical classes)
Assessment methods
written examination
Language of instruction
English
Further comments (probably available only in Czech)
The course can also be completed outside the examination period.
Teacher's information
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)
The course is also listed under the following terms Spring 2020, Autumn 2020, Autumn 2022, Autumn 2023, Autumn 2024.
  • Enrolment Statistics (Autumn 2021, recent)
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