# Class Activity #9 – Chapter 16 – Regression – Hybrid Methods II

Class Activity #9 – Chapter 16 – Regression – Hybrid Methods II

Circle One:      Monday                       Wednesday                             Friday

Instructions: Read the following scenario, and then answer the questions that follow. Note: This is a lot like you individual Regression Assignment (#7), so pay close attention! I’ll fill in some of the numbers for you here, but you are on our own with Assignment #7

One widely held belief regarding men is that the taller they are, the more attractive women rate them! Imagine a researcher measures men’s height and independently has women rate each man’s level of attractiveness (0 = Not at all attractive to 10 = Extremely attractive). The researcher finds the following data:

 Height (X) in inches Attractiveness (Y) 0 to 10 scale X2 Y2 XY 72 10 5184 100 720 70 8 4900 64 560 70 9 4900 81 630 73 10 5329 100 730 69 9 4761 81 621 69 8 4761 64 552 70 7 4900 49 490 71 8 5041 64 568 70 8 68 6 Total ∑

1. What is the independent variable (the variable we know, or the predictor)? What is the dependent variable (the variable we are predicting, or the criterion variable)? WHY?

1. What is the regression weight (b)? Show your work. That is, calculate b

1. What is the regression intercept (a)? Show your work. That is, calculate a

1. First, what is the regression equation (Y’)? Just give me the formula here. Second, show me the formula with your a and b numbers from Question 1 and 2 above as part of the equation.

1. If Steve is 67 inches tall, what attractiveness rating do we predict women will assign to him? Show your steps, rounding to two decimal places!

1. Now verify your answers by running a regression analysis in SPSS. Did you obtain the same results? Is the association significant?