A Statistical test provides a mechanism for making quantitative decisions about a process or processes. Its intent is to determine whether there is enough evidence to reject a null hypothesis or hypothesis about the process. The course will cover designing the statistical testing process, data preprocessing, understanding and interpreting the basic statistical concepts (p-value, confidence interval, etc.), and the most common statistical testing methods in clinical research. The course will also include a hands-on component using GraphPad Prism and R statistical language to perform common statistical tests.
- Introduction to statistical testing process
- Data Preprocessing
- Common parametric and non-parametric tests, including two-sample t-test, ANOVA, multiple comparisons, correlation, linear regression, Robust statistics, etc.
- Application in GraphPad Prism and R
- Location: A/322, Rocky Mountain Laboratories, Hamilton, Montana, United States
- Time: Wednesday, Sep 11, 2019, 11:00 AM - 3:00 PM [MDT]
- Presenter: Qinlu Wang (qinlu.wang@nih.gov)
- bioinformatics @NIAID - BCBB website with training materials, apps, and the services we provide.
- Suggest a statistical class! Fill the survey and suggest the statistical topics you would like to learn
- Email bioinformatics@niaid.nih.gov or me if you any questions about your particular data or project