SPSS OUTPUT BASED QUESTIONS

REGRESSION OUTPUT

Variables Entered/Removeda
Model	Variables Entered	Variables Removed	Method
1	Attitude towards internet, Familiarity with the internet, Gender, Attitude towards technologyb	.	Enter
a. Dependent Variable: Internet usage in hours per week
b. All requested variables entered.

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.922a	.852	.825	1.89643
a. Predictors: (Constant), Attitude towards internet, Familiarity with the internet, Gender, Attitude towards technology

ANOVAa
Model	Sum of Squares	Df	Mean Square	F	Sig.
1	Regression	445.289	4	111.322	30.953	.000b
Residual	89.911	25	3.596
Total	535.200	29
a. Dependent Variable: Internet usage in hours per week
b. Predictors: (Constant), Attitude towards internet, Familiarity with the internet, Gender, Attitude towards technology

Coefficientsa
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	-.457	3.112		-.147	.884
Attitude towards technology	1.370	.406	.446	3.373	.002
Familiarity with the internet	1.509	.272	.610	5.559	.000
Gender	-1.506	.917	-.178	-1.643	.030
Attitude towards internet	-.708	.499	-.185	-1.417	.040
a. Dependent Variable: Internet usage in hours per week

Questions

Interpret the value of R Square (in the Table above) for the tested model.

1. What is the hypothesis being tested in the ANOVA table with respect to the model?

1. What will be the final regression equation used for predicting dependent variable from given values of independent variables?
   1. Write the null and alternate hypotheses for the problem given above.

CROSS-TABS & CHI-SQUARE OUTPUT

The analysis given below is carried out between in-store promotion and normalized sales.

Case Processing Summary
	Cases
Valid	Missing	Total
N	Percent	N	Percent	N	Percent
InStorePromotion * NormalizedSales_Categorical	60	100.0%	0	0.0%	60	100.0%

InStorePromotion * NormalizedSales_CategoricalCrosstabulation
	NormalizedSales_Categorical	Total
1.00	2.00
InStorePromotion	High	Count	0	20	20
% within InStorePromotion	0.0%	100.0%	100.0%
Medium	Count	8	12	20
% within InStorePromotion	40.0%	60.0%	100.0%
Low	Count	16	4	20
% within InStorePromotion	80.0%	20.0%	100.0%
Total	Count	24	36	60
% within InStorePromotion	40.0%	60.0%	100.0%

Chi-Square Tests
	Value	Df	Asymp. Sig. (2-sided)
Pearson Chi-Square	26.667a	2	.000
Likelihood Ratio	33.825	2	.000
Linear-by-Linear Association	26.222	1	.000
N of Valid Cases	60
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 8.00.

Questions

1. How is thePearson Chi-Square valuecalculated in the problem given above?