Avoiding Pitfalls in Hypothesis Testing: A Singapore H2 Math Guide

Avoiding Pitfalls in Hypothesis Testing: A Singapore H2 Math Guide

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Frequently Asked Questions

Forgetting to define the null and alternative hypotheses clearly before conducting the test.
Understand that a p-value indicates the probability of observing the test statistic (or a more extreme value) if the null hypothesis is true, not the probability that the null hypothesis is true.
Type I error is rejecting a true null hypothesis, while Type II error is failing to reject a false null hypothesis. Understand the consequences of each in the context of the problem.
Identify the type of data (e.g., continuous, categorical), the number of samples, and whether the samples are independent or paired.
A larger sample size generally increases the power of the test, making it more likely to detect a true effect if one exists.
Avoid stating that you have proven the alternative hypothesis. Instead, state whether there is sufficient evidence to reject the null hypothesis.
Investigate outliers to determine if they are genuine data points or errors. Consider using robust statistical methods if outliers are present.
Encourage them to practice a variety of problems, understand the underlying concepts, and seek help from tutors or teachers when needed.