1. Course Review

2. Distributions What are the important aspects needed to describe a distribution of one variable? List three types of graphs that could be used to display a one-variable distribution. Name two easy ways to check if a distribution is approximately normal. In a skewed distribution, how does median relate to mean?

3. Regression When would you use linear regression? What is r? What values can it take on? What does r 2 tell you? What is the meaning of a? What is the meaning of b? What important technique gives evidence that a linear model is appropriate? What IS a residual? What are the two important non-linear models we studied? How could you guess which is appropriate in a particular situation? For the those non-linear models we studied, how do you linearize the data and get the mathematical model?

4. The mechanics of finding each model Linear Use L 1 & L 2 x list y list The model is: y = a + bx Calc gives: a and b No conversion Polynomial Use L 4 & L 3 log(x list) log(y list) The model is: y = a x b Calc gives: A and b Convert 10 A =a Exponential Use L 1 & L 3 x list log(y list) The model is: y = a b x Calc gives: A and B Convert 10 A =a and 10 B =b

5. Experiments and Studies What is the difference between a study and an experiment? Define a probability sample. What are the three elements that MUST be present in any experiment? What does double-blind mean? What are the five steps of a simulation?

6. Probability Write a definition of probability. What is a sample space? What is the sum of probabilities in the sample space? What are independent events? What are disjoint events? Write the full OR probability formula. Write the full AND probability formula.

7. Random Variables What is a discrete random variable? How is it different from a continuous r.v.? What is a p.d.f.? A c.d.f.? How are they displayed? How is a continuous r.v. displayed? What is the expected value of a discrete random variable? What is the binomial setting? What is the geometric setting?

8. Inference What is a sampling distribution? Describe the sampling distribution for sample means if X is N(μ,σ). Describe the sampling distribution for sample proportions if the population proportion is p. Describe the logic of hypothesis testing. Describe the meaning of a C% confidence interval.

9. Assumptions What must be true for hypothesis tests and confidence intervals for means? What must be true for hypothesis tests and confidence intervals for proportions? What must be true for hypothesis tests for distributions? What must be true for hypothesis tests for linear regression?

10. Assumptions Summary Procedure One population t for means Two population t for means One population z for proportions Two population z for proportions X 2 test for distributions t procedures for linear regression Assumptions SRS, Normal Dist SRS, Normal, Independent SRS, large pop, 10 succ/fail SRS, large pop, 5 s/f each SRS, expect each count at least 1 –No more than 20% less than 5 SRS, Association is linear; response variable varies normally about the LSRL with constant standard deviation.

11. 5 Steps to Score a 4! 1.State the procedure appropriate to the problem 2-population t-test for means 1-population z interval for proportions Chi-squared test for distributions etc! 2.State the assumptions needed for the test and verify that they are met 3.State hypotheses and significance level 4.Perform the calculation; state the test statistic value and the p-value Formula: show all work Calculator: state screen used and results Explicitly state the statistic (z or t or X 2 ) and p value 5.State your conclusion in the context of the problem 1.Remember the 3-phrase form for tests or intervals