R: Recipes for Analysis, Visualization and Machine Learning

Conducting an exact binomial test

While making decisions, it is important to know whether the decision error can be controlled or measured. In other words, we would like to prove that the hypothesis formed is unlikely to have occurred by chance, and is statistically significant. In hypothesis testing, there are two kinds of hypotheses: null hypothesis and alternative hypothesis (or research hypothesis). The purpose of hypothesis testing is to validate whether the experiment results are significant. However, to validate whether the alternative hypothesis is acceptable, it is deemed to be true if the null hypothesis is rejected.

In the following recipes, we will discuss some common statistical testing methods. First, we will cover how to conduct ...