Class Activity #9 – Chapter 16 – Regression – Hybrid Methods II
Class Activity #9 – Chapter 16 – Regression – Hybrid Methods II
Circle One: Monday Wednesday Friday
Your Names: __________________________________________________________________
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 |
X^{2} | Y^{2} | 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 ∑ |
- 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?
- What is the regression weight (b)? Show your work. That is, calculate b
- What is the regression intercept (a)? Show your work. That is, calculate a
- 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.
- 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!
- Now verify your answers by running a regression analysis in SPSS. Did you obtain the same results? Is the association significant?