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In your t-test results, pay attention to the p-value. If it's less than your chosen alpha level (e.g., 0.05), you can reject the null hypothesis. A small p-value indicates a significant difference between the groups.
In chi-square tests, focus on the p-value and the test statistic. A small p-value (usually < 0.05) indicates a significant difference or association, while a larger p-value suggests no significant difference or association.
Always interpret your results in the context of your research question. What does a significant result mean for your study?
By following these steps and using the appropriate R functions for t-tests and chi-square tests, you'll be equipped to analyze and draw meaningful conclusions from your data, whether you're comparing means or exploring relationships between categorical variables.
