Practice Best Practices - 4.7 | 4. Statistical Inference and Hypothesis Testing | Data Science Advance
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4.7 - Best Practices

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is one assumption that should be verified before conducting a statistical test?

💡 Hint: Think about the distribution of your dataset.

Question 2

Easy

Why is it important to report effect sizes?

💡 Hint: How does effect size compare to p-value?

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What is the primary purpose of verifying assumptions in statistical testing?

  • To ensure data fits the model assumptions.
  • To increase the sample size.
  • To ignore outliers.
  • To maximize p-values.

💡 Hint: Think about what assumptions are necessary for accurate testing.

Question 2

True or False: Effect sizes are irrelevant to hypothesis testing.

  • True
  • False

💡 Hint: Consider what additional insights effect sizes provide beyond p-values.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You conducted three different tests on the same dataset. The p-value for each test was 0.04. Explain how you would apply the Bonferroni correction in this scenario.

💡 Hint: Remember the formula for the Bonferroni correction.

Question 2

Critically evaluate a scenario in which assuming normality might lead to a potential error in results. What would be a practical approach to handle non-normal data?

💡 Hint: Think about which tests are designed for non-normal conditions.

Challenge and get performance evaluation