For sample n>30, the degree of freedom is n-1. 


True

False


**False.**

For a sample size of \( n > 30 \), the degrees of freedom (df) is still \( n - 1 \), not just for large sample sizes. This applies generally in basic statistical calculations such as when estimating population parameters using a sample, specifically in cases like the calculation of the sample standard deviation or in a t-distribution for hypothesis testing.

Would you like more details or have any questions?

Here are 5 related questions:
1. What is the significance of degrees of freedom in statistical analysis?
2. How is the t-distribution affected by the degrees of freedom?
3. Why is the formula for degrees of freedom in small samples also \( n-1 \)?
4. How does degrees of freedom apply to different types of tests (e.g., chi-square test)?
5. What is the difference in using the t-distribution versus the z-distribution?

**Tip**: When dealing with large sample sizes, the t-distribution approaches the normal distribution as the degrees of freedom increase.

For sample n>30, the degree of freedom is n-1. True or False?

This page provides a clear explanation on how to calculate degrees of freedom when the sample size is greater than 30. Learn the key concepts of degrees of freedom and how they apply to statistical analysis, including hypothesis testing and t-distribution. Suitable for high school and college statistics students.

Math Problem Statement

Solution

Ask a new question for Free

By Image

Math Problem Analysis

Mathematical Concepts

Formulas

Theorems

Suitable Grade Level

Related Recommendation