Biostatistics

Introduction to statistical methods useful for data summary and evaluation of experimental results. Demonstration of spreadsheets and dedicated software for data analysis. Knowledge about experimental design and basic statistical approaches to analyze data collected from experiments and how to handle the data using computer software. Student will learn statistical functions built in Excel (Libre Office) and in dedicated software, various procedures of data management and interpretation of the results.

Students will learn principles of data management, how to summarize variables and present collected data and results. They will learn how to design experiments and apply advanced statistical methods for their analyses, interpret results considering estimation errors, and explore relationships between variables. They will perform statistical analyses using spreadsheet and statistical software and they will present results of a case study analyses of their choice

Introduction to statistical methods useful for data summary and evaluation of experimental results. Demonstration of spreadsheets and dedicated softwares for data analysis. Knowledge about experimental design and basic statistical approaches to analyze data collected from experiments and how to handle the data using computer software. Student will learn statistical functions built in Excel and in dedicated software, various procedures of data management and interpretation of the results.

Students will learn principles of data management, how to summarize variables and present collected data and results. They will learn how to design experiments and apply advanced statistical methods for their analyses, interpret results considering estimation errors, and explore relationships between variables. They will perform statistical analyses using spreadsheet and statistical softwares and they will present results of a case study analyses of their choice.

Variables, scales, distributions, sampling

Descriptive statistics

Sampling, estimation, errors

Experimental design, sources of variation

Analysis of variance

Regression

Non-parametric tests

Data management in spreadsheets

Calculation of descriptive statistics

Data and results visualization

Testing statistical hypotheses based on mean comparison Analysis of variance of different experimental designs

Analysis of regression and correlation

Case study presentation

Electronic Statistical Textbook, Statsoft:

http://www.statsoft.com/textbook/

University of Reading Statistical Service Centre: http://www.reading.ac.uk/ssc

Knowledge and understanding The student knows methods of data description, available methods of data analysis for comparison purposes, basic exploratory techniques, principles of experimental design.

Reflection The student is capable of formulating statistical hypotheses, interpreting the output of statistical analyses.

Transferable skills – not tied to just one subject Teamwork, ability to write reports and present them to the public.

- Written exam (30%)

- Preparation and presentation of Reports (70%)

both parts must be passed

Evaluation scale: Grades from 2.0 (worst) to 5.0 (best)