Hypothesis testing is a fundamental concept in statistics. It allows us to make inferences about a population based on a sample. In this tutorial, we will explore the basics of hypothesis testing, including types of hypotheses, test statistics, and p-values.

Types of Hypotheses

There are two types of hypotheses in hypothesis testing:

  • Null Hypothesis (H0): This is the hypothesis that we want to test. It usually states that there is no significant difference or effect.
  • Alternative Hypothesis (H1): This is the hypothesis that contradicts the null hypothesis. It states that there is a significant difference or effect.

Steps of Hypothesis Testing

The process of hypothesis testing involves the following steps:

  1. State the hypotheses: Clearly define the null and alternative hypotheses.
  2. Choose a significance level: This is the probability of rejecting the null hypothesis when it is true. Common significance levels are 0.05 and 0.01.
  3. Collect data: Gather data from a sample.
  4. Calculate the test statistic: Use the data to calculate a test statistic that measures the difference between the observed data and the expected data under the null hypothesis.
  5. Determine the p-value: The p-value is the probability of obtaining a test statistic as extreme as or more extreme than the one observed, assuming the null hypothesis is true.
  6. Make a decision: Compare the p-value to the significance level. If the p-value is less than the significance level, reject the null hypothesis. Otherwise, fail to reject the null hypothesis.

Example

Suppose we want to test whether a new drug is effective in reducing blood pressure. The null hypothesis (H0) is that the drug has no effect, and the alternative hypothesis (H1) is that the drug reduces blood pressure.

We collect data from a sample of patients and calculate the test statistic. If the p-value is less than 0.05, we reject the null hypothesis and conclude that the drug is effective.

Further Reading

For more information on hypothesis testing, you can read our comprehensive guide on Hypothesis Testing.

Hypothesis Testing