Statistical Comparisons using R
This practical workshop will help participants to choose and use the appropriate standard statistical test for their data by introducing key concepts of inferential statistics in R. Participants will learn how to compute and interpret hypothesis tests for popular statistical models such as correlation, contingency tables, chi-square test, t-test and ANOVA.
Recommended Participants
Researchers wanting to understand how to choose the right statistical test for the context/condition and how to conduct the analysis by themselves using R. The workshop is relevant for all disciplines, although examples and exercises will be based around biological and clinical datasets.
Prior expertise with R and the command line interface is required to a level equivalent to that provided by the R for Reproducible Scientific Analysis workshop, as the basics of R will not be covered.
Learning Objectives
Choose the right statistical test appropriate for the data and the research questions
Carry out inferential statistics in R
Generate plots, figures and tables of hypothesis tests using specific R packages
Interpret and report the results of a range of commonly-used statistical tests
Syllabus
An introduction to hypothesis testing terminology
Correlation analysis between two continuous variables
Statistical tests for both categorial and continuous variables
ANOVA - testing with more than two groups
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