Can inferential statistics be used to test a hypothesis?

Can inferential statistics be used to test a hypothesis?

• A. Yes
• B. No
• C. Only for descriptive data
• D. Only with a random sample

Answer: (A)

Inferential statistics are used to test hypotheses about a population using sample data. They let you determine whether the observed results are likely due to random variation or reflect a real effect. The process involves setting up a null hypothesis, choosing an appropriate test, calculating a test statistic and p-value, and deciding whether to reject the null. This goes beyond simply describing the data, which is what descriptive statistics do; description summarizes what happened in the sample, while inference asks what would likely happen in the broader population. An example: you want to know if a new treatment changes blood pressure. You state a null hypothesis that there is no change, collect a sample, run the appropriate test, and if the p-value is below your threshold, you conclude there is evidence of a treatment effect. The idea that it is limited to descriptive data is incorrect, and while random sampling strengthens the validity of generalizing results, inference can still be used with other sampling plans, though conclusions about the population should be drawn with caution.

Inferential statistics are used to test hypotheses about a population using sample data. They let you determine whether the observed results are likely due to random variation or reflect a real effect. The process involves setting up a null hypothesis, choosing an appropriate test, calculating a test statistic and p-value, and deciding whether to reject the null. This goes beyond simply describing the data, which is what descriptive statistics do; description summarizes what happened in the sample, while inference asks what would likely happen in the broader population.

An example: you want to know if a new treatment changes blood pressure. You state a null hypothesis that there is no change, collect a sample, run the appropriate test, and if the p-value is below your threshold, you conclude there is evidence of a treatment effect.

The idea that it is limited to descriptive data is incorrect, and while random sampling strengthens the validity of generalizing results, inference can still be used with other sampling plans, though conclusions about the population should be drawn with caution.