Learn about confidence intervals and hypothesis tests for one and two variances, assuming normally distributed populations. Explore the sampling distribution of sample variance and derive confidence intervals for variances and their ratios. Examine examples of confidence intervals and hypothesis tests for both single and two-variance scenarios. Investigate the robustness of these statistical procedures when the normality assumption is violated. Gain insights into the limitations and potential pitfalls of these methods when applied to non-normal distributions.
Overview
Syllabus
An Introduction to Inference for One Variance (Assuming a Normally Distributed Population).
Inference for One Variance: An Example of a Confidence Interval and a Hypothesis Test.
The Sampling Distribution of the Sample Variance.
Deriving a Confidence Interval for a Variance (Assuming a Normally Distributed Population).
An Introduction to Inference for the Ratio of Two Variances.
Inference for Two Variances: An Example of a Confidence Interval and a Hypothesis Test.
Deriving a Confidence Interval for the Ratio of Two Variances.
The Sampling Distribution of the Ratio of Sample Variances.
Inference for a Variance: How Robust are These Procedures?.
Inference for the Ratio of Variances: How Robust are These Procedures?.
Taught by
jbstatistics
