The lecture Sampling Distributions for Proportions and Means by David Spade, PhD is from the course Learn Statistics  Become Data Smart. It contains the following chapters:
Which statement accurately describes a sampling distribution?
What is not one of the conditions necessary for the normal model to approximate the distribution of a sample proportion?
What is not true regarding the central limit theorem?
Consider a random sample of size 100 with a mean of 5 and a standard deviation of 10. What are the mean and the standard deviation of the distribution of the sample mean?
What is true regarding the sampling distributions of means and proportions?
If the population size is 10,000 then what sample size is required to meet the 10% condition?
In which case is the success/failure condition met?
According to the central limit theorem, what sample size is sufficient to assume that the data is normally distributed?
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