# Chi-Square, Multiple Regression

1) A survey was conducted at a university. 30 students randomly selected and asked if they watched football. Their answers (Y=yes, N=no) and their sex (M=male, F=female) follows:

Viewing:YNNYYYNYYNYNNYYYNNYNNYNNNYNYNN

Sex :MFFMFFMMFMMFFMFMMFMMFMFFFFFMMF

Test the hypothesis that "watching football" is independent of "Gender", using 0.01 level of significance.

2) Assume sample size = 20. The CEO of a large appliance manufacturer believes that annual national expenditure on home appliances is linearly related to national personal disposable income. She collects data and estimates the equation as

Yi= -5.978 + 0.072 Xi R^2 = 0.95

(2.821) (0.0006)

a) Test Ho: B1=0 against B1 not equal to 0. using alpha 0.05.

b) Estimate expenditure on appliances if disposable income is $ 900

3) A financial analyst using 25 annual observations estimates the following linear regression model:

Yt=-509 + 0.89 X1t + 17.27X2t - 21.20X3t - 0.522X4t + 7.36X5t

(23.4) (3.24) (53.46) (0.175) (5.69)

Where Y is yearly Dow Industrial Average (DJIA)

X1 is ratio of corporate profit to corporate sales

X2 is index of industrial Production

X3 is Corporate bond yield

X4 is per capita Disposable Income

X5 is consumer price index

a) Do any of the coefficients appear to have the wrong sign?

b) Which variable(s) appear to have no significant impact on the DJIA?

https://brainmass.com/statistics/regression-analysis/chi-square-multiple-regression-137993

#### Solution Summary

The solution tests hypotheses and determines the chi-square and multiple regression.