General Topics You Should be Comfortable With:
• If you struggled at all with descriptive statistics (mean, median, mode, sd, variance) you should review those concepts.
• Population vs. sample
• Sampling:
o Logic behind samples
o Errors associated with sampling
o Notations to represent sample vs. population
o Types of samples: what they are, why we use them, benefits / drawbacks of each
• Sampling distributions / distribution of means
• Central limit theorem
• Confidence Intervals
o What they are
o Levels of confidence
o How social scientists report confidence
o How to calculate a confidence interval
• Hypothesis testing
o Difference between the null and the research hypothesis, and how to report each
 How do you know when to reject or fail to reject the null hypothesis?
o Type I vs. Type II errors
o Levels of significance
 What does this mean?
 Why do we set levels of significance?
 Fisher’s p-value
 Critical region
• T-tests (fun fact: I used t-tests to analyze the data for my Master’s thesis)
o Why do we do them? What are they testing?
o Know the null / alternative hypotheses associated with the types of t-tests
o Know the assumptions of each type of t-test
o Know how to interpret the SPSS output from a t-test

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