NOTE: This is not an exhaustive list of questions that may be asked, but being prepared to answer these will greatly help you.

Study Design

What is the difference between an experiment and observational study? How does this affect conclusions?

What determines whether we can make generalizations about our conclusions?


Confidence Intervals

What is the purpose of a confidence interval?

What does “confidence” actually mean?

What type of variability do CIs account for?

Explain the relationship between confidence level and interval width

Explain the relationship between sample size and interval width

How do width of CIs using the normal distribution compare to t-distribution CIs for the same confidence level

When do we use t- vs. Normal distribution for CIs?

Explain the 68-95-99.7% Rule

What is a sampling distribution?

What is the Margin of Error?

Briefly explain what the CLT tells us


General Hypothesis Testing

What different types of questions do CIs and Hypothesis testing answer?

Describe the difference between the Null hypothesis and the Alternate hypothesis. Which one are we trying to show is true?

Why do we calculate a test-statistic?

What does the test-statistic tell us in the context of a hypothesis test?

Why do we sometimes call tests left, right, or two-tailed tests?

What is the definition of a p-value? (SUPER IMPORTANT)

What does the p-value tell us for a hypothesis test?

How does the sample size affect the test-statistic, and as a consequence the p-value, with everything else held constant?

How does the standard error affect the test-statistic, and as a consequence the p-value, with everything else held constant?

What is the difference between ‘statistical significance’ and ‘practical significance’?


Decision Making

What does the ‘significance level’ refer to in hypothesis testing?

What is a Type I error and what is another name for it?

What is a Type II error and what is another name for it?

What type of error occurs if H0 is False but we fail to reject it?

What type of error occurs if H0 is True but we do reject it?

Explain why using \(\alpha\) = 0.05 as a strict cut-off for significance is problematic

What should determine the value we use for our significance level of a hypothesis test?

Explain in your own words what is meant by the following phrase: “Over time it appears the p-value has become a gatekeeper for whether work is publishable.”