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: the null hypothesis and the 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 an exact binomial test in R.
Getting ready
Since the binom.testfunction originates from the stats package, make sure the stats library is loaded.
How to do it...
Perform the following steps:
- Assume there is a game where a gambler can win by rolling...
