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

4.7 - Best Practices

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Practice Questions

Test your understanding with targeted questions

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?

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

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