Hypotheseis Tests and Binominal Distributions

Hypothesis tests involving binomial distributions are used for analysing discrete data with two possible outcomes.
These distributions are defined by the probability of success (p), and the total number of trials (n).
The null hypothesis typically presumes a specific probability of success.
The alternative hypothesis could suggest that the success probability is greater, lesser, or not equal to the null hypothesis value.
A test statistic, calculated using sample data, is used to carry out the test.
The critical region, significance level, or p-value help decide whether to accept or reject the null hypothesis.
Effectively conducting hypothesis tests with binomial distributions is beneficial for data analysis in various fields.