The theoretical difference between permutation tests and inferential tests is that with permutation tests we build the sampling distribution from the observed data, rather than inferring or assuming that a sampling distribution exist. Permutation tests are a type of randomization test. 14.3 Permutation test for a Paired t-test.
14.2 Correlation Coefficient Permutation Tests.13.7.3 Calculating 95% confidence interval of ‘b’ by hand.13.7 Examining individual predictor estimates.Homogeneity of Variance / Homoscedasticity 13.4.1 What to do with the Standard Error of the Estimate ?.13.3.3 Comparing our trendline to other trendlines.
Permutation test how to#
13.2.2 How to calculate a and b ‘by hand’. 12.4 Assumptions of Pearson’s Correlation. 12.3.1 Significance Testing a Pearson Correlation. 12.3 Conducting a Pearson Correlation Test. 11.12 Non-parametric Alternatives to the Two Sample t-tests. 11.11 Non-parametric Alternatives for Independent t-tests. 11.10.1 The paired t-test is a one-sample t-test. 11.9 Effect Size for Independent two sample t-tests:. 11.7 Assumptions of the Independent t-test. 11.6 Conducting the Student t-test in R. 11.5 Confidence Interval for Difference in Means. 11.2.1 Visualizing the Sampling Distribution. 11.2 Sampling Distribution of the Difference in Sample Means. 10.4 Assumptions of the one-sample t-test. 10.3 Conducting one-sample t-tests in R. 10.2.1 Critical values for the one-sample t-test. 8.5 Comparing CIs using the z- and t-distributions. 8.4.2 Other Confidence Intervals ranges for t-distribution. 8.4.1 t-distribution CIs and sample size. 8.4 Calculating a t-distribution Confidence Interval. 8.3 Confidence Intervals with t-distribution. 8.2.2 Confidence Intervals and Sample Size. 8.2.1 Other Confidence Intervals ranges. 8.2 Calculating a confidence interval with z-distribution. 7.2.1 Sample Size and the Sampling Distribution. 7.1.2 Using z-scores to determine probabilities. 6.4.8 Sample versus Population Standard Deviation. 6.4.6 Average versus Standard Deviation. 5.8 Saving and Exporting ggplot2 graphs. 5.5 Comparing Distributions across Groups. 4.5.3 select() - Selecting specific columns. 4.1.2 Numerical Data (Discrete vs. Continuous). 3.7 Some things that are useful to know. 1.5 Other places to find help about R and Statistics. 1.1 What this book includes and what it doesn’t.
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