Study Questions

Exam I Review:

Sampling

What is the difference between a sample and a population?

What is the difference between a sample and a sampled population?

What is the difference between a variable and data?

If a sample is large enough will it be representative of the target population?

Why is important that samples be representative of the target population?

What kinds of errors can bias the results of a poll?

What is the difference between a sample of convenience and a random sample? Give an example of each.

What is the difference between random samples and random assignment of subject to treatment in a designed experiment? Are all designed experiments based on random samples?

Exam II Review:

Descriptive Statistics

Why do we use the sample mean instead of the sample median to estimate the mean of a population? Why is the median sometimes preferred?

What is a robust statistic? Why is a robust statistic better than a non-robust statistic?

Exam III Review

Probability and distributions

What is the difference between a probability distribution and a sampling distribution?

What is the difference between the standard deviation and the standard error?

What is the Central Limit Theorem and why is it useful?

When is the sampling distribution of the mean normally distributed? What if the sample size is small? What if is large? What if the parent population is normal? What if it isn't?

What is bias? When is the sample mean an unbiased estimator of the population mean? When is the sample variance unbiased for the population variance? When is the sample median unbiased for the population mean?

What are the benefits of increasing sample size for a hypothesis test? What is the benefit of increasing sample size for confidence intervals?

What is the interpretation of a confidence interval?

Given only the sample size how do you calculate the margin of error of a survey or poll? What is the margin of error of a poll conducted with a random sample of 100 subjects?

What are the assumptions necessary for a one sample hypothesis test to be valid? What assumptions are necessary for each of the hypothesis tests we've covered in class?

When the p-value is smaller than we conclude that "We reject the null hypothesis and conclude the alternative hypothesis is true". But when the p-value is larger than we conclude that "We fail to reject the null hypothesis since there was insufficient evidence to prove the alternative was true". In the latter case (when we fail to reject the null) why don't we say "We conclude the null hypothesis is true"? (Think about it for a while and then look at my answer)