The five steps of hypothesis testing are stating the null and alternative hypotheses, determining the test statistic, finding the probability of test statistics, determining the level of statistical significance, and making a conclusion about the hypotheses. Hypothesis testing allows the validity of a hypothesis to be determined with statistics.
Stating the null and alternative hypotheses is an essential first step, because this is what you're going to test. The alternative hypothesis is what you think the data will show, and should be based on previous data or an educated guess. The null hypothesis is the case where that is not true.
Determining the test statistic means choosing between doing a Z test or a t test. The t test is more commonly used because, unlike the Z test, it is not necessary to know the standard deviation.
Determining the probability of test statistics means computing what is known as the p-value. Methods for computing the p-value are different depending on the type of distribution being used. The level of statistical significance can be determined based on the p-value. The lower the p-value, the better. Typically, p-values should be below 0.05 for the result to be statistically significant.
After completing these steps, a conclusion can be reached about the hypothesis that has been tested.