A researcher can use statistical software to conduct a hypothesis test by following these steps:

1. State the Hypotheses: Define the null hypothesis (H₀) and alternative hypothesis (H₁).

2. Select the Test: Choose an appropriate statistical test (e.g., t-test, ANOVA, chi-square) based on the research question and data type.

3. Input Data: Enter the dataset into the software, ensuring it is clean and formatted correctly.

4. Check Assumptions: Use diagnostic tools in the software to verify that assumptions (e.g., normality, independence) are met.

5. Perform the Test: Use the software's testing function to run the analysis. Specify parameters such as significance level (commonly α = 0.05).

6. Interpret Results: Examine the output, including p-values and test statistics, to determine whether to reject or fail to reject H₀.

7. Report Findings: Summarize the results, highlighting key values and their implications for the research question.

Common statistical software like SPSS, R, or Python automates calculations and provides visualizations to aid interpretation.