Foundations for Inference: Point Estimates

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0:00 - Introduction
0:37 - Point Estimates, Error, and Bias
1:42 - What is a Sampling Distribution?
5:20 - Central Limit Theorem
8:38 - Example Utilizing the Central Limit Theorem
11:01 - When We Don't Know p (Population Proportion)
12:46 - Sampling Distribution Under Different Scenarios
16:53 - Extending These Ideas to Other Contexts
17:48 - Recap
18:30 - Hello, Friends
  1. OpenIntroOrg
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Your work in openintro is wonderful, and your videos are amazing. I'm a PhD student improving my statistics base with OpenIntro Statistics. Thank you very much for your help and please don't stop making it.

gustavosabbag
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Have a question on 5.6b repeated student samples in this chapter of 5.1. Can we expect that the distribution is normal only when np and n(1-p) is equal or greater than 10? Because in 5.6, 0.16(0.4) does not result in a number greater than 10.

michaelvosvigen
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In the diagram of the normal distribution with mean 0.88, why was the two other points .86 and .90?

masterevill
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