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Statistical Analysis in R
222 studentsINTERMEDIATEEnglish
Korshub's take
Statistics Put to Work
Statistical inference isn't just theoretical—it's the framework you use when you need answers from data. This course builds your toolkit: confidence intervals, hypothesis testing, and the specifics of when each method applies. You'll dig into ANOVA with diagnostics, use simulations and permutation tests to explore distributions, and move through linear regression, ANCOVA, and generalized linear models. Power analysis and experimental design ensure you're thinking about sample size and study structure before you collect data.
About this course
Basics of statistical inference, confidence intervals and hypothesis testing. Commonly used tests. Pvalues, statistical and practical significance. ,Analysis of Variance (ANOVA) and post-hoc tests. Diagnostics, implementation and interpretation using R. ,Numerical Methods: The use of simulations, nonparametric bootstrap and permutation tests using R. ,Linear Regression, Analysis of Variance with Covariates (ANCOVA), Generalised Linear Models (GLMs) and Mixed Effects Linear models using R. ,Basics of power analysis (sample size evaluation) and some thoughts on experimental design.
Price
$618
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