Unit 9 - Lesson 2

Question 1

Central Limit Theorem

Answer 1

Even in the original distribution you are sampling from isn’t normal, if you take large enough samples from it (n ≥ 30), the sampling distribution created will resemble a normal distribution.

If you take larger samples, the sampling distribution will more closely resemble a normal distribution (because the SD would be lower)

Question 2

When can you assume a sample distribution is roughly normal?

Answer 2

If the sample size is ≥ 30, then the sample distribution will be roughly normal. That way, you can make assumptions about it.

For example, if nightly sleep times are distinctly non-normal but you have a sample size of 100, the sample distribution of sleep times would be roughly normal.

Why would the SAMPLE distribution be normal while the population distribution isn’t? Because a renowned statistician said so. No, really.