Explain in detail the process of hypothesis testing.
Answers
Explanation:
Hypothesis testing is generally used when you are comparing two or more groups.
Five Steps in Hypothesis Testing:
Step 1: Specify the Null Hypothesis
The null hypothesis (H0) is a statement of no effect, relationship, or difference between two or more groups or factors. In research studies, a researcher is usually interested in disproving the null hypothesis.
Step 2: Specify the Alternative Hypothesis
The alternative hypothesis (H1) is the statement that there is an effect or difference. This is usually the hypothesis the researcher is interested in proving. The alternative hypothesis can be one-sided (only provides one direction, e.g., lower) or two-sided. We often use two-sided tests even when our true hypothesis is one-sided because it requires more evidence against the null hypothesis to accept the alternative hypothesis.
Step 3: Set the Significance Level
The significance level (denoted by the Greek letter alpha— a) is generally set at 0.05. This means that there is a 5% chance that you will accept your alternative hypothesis when your null hypothesis is actually true. The smaller the significance level, the greater the burden of proof needed to reject the null hypothesis, or in other words, to support the alternative hypothesis.
Step 4: Calculate the Test Statistic and Corresponding P-Value
In another section we present some basic test statistics to evaluate a hypothesis. Hypothesis testing generally uses a test statistic that compares groups or examines associations between variables. When describing a single sample without establishing relationships between variables, a confidence interval is commonly used.
Step 5: Drawing a Conclusion
- P-value <= significance level (a) => Reject your null hypothesis in favor of your alternative hypothesis. Your result is statistically significant.
- P-value > significance level (a) => Fail to reject your null hypothesis. Your result is not statistically significant.