# Question: In a survey that included assessment of husband and wife

In a survey that included assessment of husband and wife heights, Hodges, Krech & Crutchfield (1975) reported the following results. Let’s treat wife height as the predictor (X) variable, and husband height as the outcome (Y) variable

rxy = .32

Wife height: Mx = 64.42, sx = 2.56

Husband height: My = 70.46, sy = 2.87

N = 1296

a. Calculate the values of the b0 and b coefficients to predict husband height in inches (Y) from wife height in inches (X) and write out this raw score predictive equation.

b. For female students. What is your own height? Substitute your own height into the equation from step a, and calculate the predicted height of your present or future spouse.

c. Now reverse the roles of the variables (that is, use husband height as the predictor and wife height as the outcome variable). Calculate the values of b0 and b to predict wife height from husband height.

d. For male students: What is your own height in inches? Substitute your own height into the equation in part c. to predict the height of your present or future spouse.

e. What is the equation to predict zy (husband height in standard score units) from zx (wife height in standard score units)? Include the numerical value of the coefficient used in this version of the equation. In your own words: what does this standardized version of the prediction equation tell us about “regression toward the mean” for predictions?

f. What proportion of variance in husband height is predictable from wife height?

g. Find SEest (for the equation from part a, prediction of husband height from wife height). What is the minimum possible value for SEest? What is the maximum numerical value that SEest could have in this research situation?

rxy = .32

Wife height: Mx = 64.42, sx = 2.56

Husband height: My = 70.46, sy = 2.87

N = 1296

a. Calculate the values of the b0 and b coefficients to predict husband height in inches (Y) from wife height in inches (X) and write out this raw score predictive equation.

b. For female students. What is your own height? Substitute your own height into the equation from step a, and calculate the predicted height of your present or future spouse.

c. Now reverse the roles of the variables (that is, use husband height as the predictor and wife height as the outcome variable). Calculate the values of b0 and b to predict wife height from husband height.

d. For male students: What is your own height in inches? Substitute your own height into the equation in part c. to predict the height of your present or future spouse.

e. What is the equation to predict zy (husband height in standard score units) from zx (wife height in standard score units)? Include the numerical value of the coefficient used in this version of the equation. In your own words: what does this standardized version of the prediction equation tell us about “regression toward the mean” for predictions?

f. What proportion of variance in husband height is predictable from wife height?

g. Find SEest (for the equation from part a, prediction of husband height from wife height). What is the minimum possible value for SEest? What is the maximum numerical value that SEest could have in this research situation?

## Relevant Questions

Here is a small set of (real) data that shows GNP per capita (X), and mean life satisfaction, for a set of 19 nations (Y). (Insert Table 9.2 about here) a. Enter the data into SPSS. b. Run the procedure; obtain the mean ...What is a multiple R? How is multiple R2 interpreted? Consider the following hypothetical data (in the file named pr1_mr2iv.sav) The research question is: How well can Systolic Blood Pressure (SBP) be predicted from Anxiety and Weight combined? Also, how much variance in blood ...Why is it acceptable to use a dichotomous predictor variable in a regression when it is not usually acceptable to use a categorical variable that has more than two values as a predictor in regression? Consider these two tables of cell means. Which one shows a possible interaction, and which one does not show any evidence of an interaction? Table 1 Table 2 Based upon these two tables, show that: a. When an interaction is ...Post your question