Inferential statistics

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Inferential statistics: 1 вопрос=1слайд
1. Define inferential statistics and explain its importance in statistical analysis.
2. What is the difference between descriptive and inferential statistics? Provide examples of each.
3. Explain the concept of sampling distribution and how it relates to making inferences and hypothesis testing.
4. Describe the Central Limit Theorem and its significance in inferential statistics.
5. Discuss the purpose and steps of hypothesis testing, including formulating null and alternative hypotheses.
6. What are Type I and Type II errors in hypothesis testing? How do they relate to the concepts of significance level and power?
7. Explain the difference between parametric and non-parametric tests. Provide examples of situations where each type would be appropriate.
8. Discuss parametric tests' assumptions, such as t-tests and ANOVA. What should be done if these assumptions are violated?
9. What are p-values, and how are they interpreted in the context of hypothesis testing? Discuss their strengths and limitations.
10. Explain the relationship between confidence intervals and hypothesis testing. How do they provide complementary information in statistical inference?