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Shape of the Sampling Distribution Video Lecture | CSIR NET Crash Course for Mathematics - CSIR NET Mathematics
FAQs on Shape of the Sampling Distribution Video Lecture - CSIR NET Crash Course for Mathematics - CSIR NET Mathematics
| 1. What is the shape of the sampling distribution? |  |
Ans. The shape of the sampling distribution is typically normal or approximately normal when the sample size is large enough according to the Central Limit Theorem.
| 2. How does the sample size affect the shape of the sampling distribution? | |
Ans. As the sample size increases, the shape of the sampling distribution becomes more normal, regardless of the shape of the population distribution.
| 3. Can the sampling distribution be skewed? | |
Ans. Yes, the sampling distribution can be skewed if the population distribution is skewed and the sample size is small.
| 4. What is the importance of the shape of the sampling distribution in statistical analysis? | |
Ans. The shape of the sampling distribution is important as it affects the accuracy of statistical tests and confidence intervals. A normal sampling distribution allows for more reliable inference.
| 5. How can one determine if the sampling distribution is approximately normal? | |
Ans. One can check the shape of the sampling distribution visually using histograms or quantitatively using measures of skewness and kurtosis. Additionally, statistical tests such as the Shapiro-Wilk test can be used to assess normality.
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Dec 22, 2024 Last updated |
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