Chapter 10: Introduction to Estimation

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Introduction to Estimation (Preview)

Length: 7 minutesAuthor: JasonComplexity: Easy

Back in Chapter 9, the Central Limit Theorem showed us that samples are typically representative of the populations from which their drawn. It follows then that the mean of a randomly selected sample should provide a fair estimate of the corresponding population mean.

Point Estimators (Preview)

Author: Jason

Using the sample mean to estimate the population mean may seem obvious, but a good estimator for a population parameter must have certain characteristics to be dependable. In this video I discuss the qualities of a good estimator: unbiasedness, consistency, and relative efficiency.

Confidence Interval Estimate of the Mean (Q1) (Preview)

Length: 26 minutesAuthor: JasonComplexity: Standard

Estimation questions are pretty easy to solve. If you can follow along the solution to the confidence interval estimation question in this video, then you’re just about prepared for the worst this chapter has to offer!

Interpreting Confidence Intervals (Q2a–b) (Preview)

Length: 16 minutesAuthor: JasonComplexity: Easy

Here’s another typical estimation question, but now we’re also asked to interpret our results. Getting this interpretation right is can be tricky – The wording has to be just right to avoid making a common mistake (which they WILL be looking for on the exam).

Sample Size Determination (Q3) (Preview)

Length: 14 minutesAuthor: JasonComplexity: Standard

If larger samples give us better estimates, then how large does a sample need to be (as a minimum) in order to ensure we keep our estimation errors small?

Multiple Choice (Preview)

Author: Jason

Test your understanding of Chapter 10: Introduction to Estimation – each question is accompanied by a mini-video lecture showing you how I decided which solution was the correct one.