What is hypothesis testing in statistics?

What is hypothesis testing in statistics?

Hypothesis testing is a statistical method used to make decisions based on data. It involves formulating a null hypothesis and an alternative hypothesis, then using sample data to determine whether to reject the null hypothesis.

Can you explain the steps involved in hypothesis testing?

Sure! The steps are: 1) State the null and alternative hypotheses, 2) Choose a significance level, 3) Collect data, 4) Calculate the test statistic, 5) Determine the p-value, and 6) Make a decision to reject or fail to reject the null hypothesis.

What is a p-value?

A p-value is the probability of obtaining test results at least as extreme as the observed results, assuming the null hypothesis is true. It helps determine the significance of the results.

What are some common types of hypothesis tests?

Common types include t-tests, chi-square tests, ANOVA, and z-tests. Each is used for different types of data and hypotheses.