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?
Explain the concept of randomization in an experiment and how it justifies causal conclusions.
Name and explain a type of sampling bias you have learned about.
Explain what correlation measures.
If a scatterplot has a value of r = .9, does that mean there must be a linear relationship between the variables? Explain.
What does the phrase ‘correlation \(\neq\) causation’ mean in your own words?
What form of relationship needs to exist between quantitative variables to perform linear regression?
Explain what extrapolation is and why we should probably try to avoid it.
What does “adjusted \(R^2\)” account for that “multiple \(R^2\)” does not in a linear model?
Describe in your own words what the Sums of Squares of Groups represents.
Describe in your own words what the Sums of Squares of Errors represents.
Describe in your own words what the F-statistic in an ANOVA test is measuring.
For basic ANOVA, describe in words what null hypothesis the F-statistic testing.
We saw that regression was a special case of ANOVA. What null hypothesis is the F-statistic testing in regression?
What issue arises when conducting multiple t-test comparisons that using an F-test solves?
Explain the concept of hypothesis testing. Avenues of thought: What is this method used for and briefly outline the logic behind it and steps needed to perform a hypothesis test.
Explain the concept of confidence intervals. Avenues of thought: What types of questions is this method used for, what problem is it solving, what does it quantify?