We want to determine whether hours spent revising, anxiety scores, and A level entry points have effect on exam scores for participants Dependent variable exam score Predictors hours spent revising, anxiety scores, and A level entry points The result of the analysis, COMPUTER output, is provided below Answer the following Determine the best fitted regression model Write the equation of the regression model (best fit model) and interpret all the Beta coefficients Interpret the ANOVA for regression fit Determine and interpret the coefficient of determination r 2 What can we conclude about the relationship of the dependent and predictor variables Regression Model Summary Model R R Square Adjusted R Square Std Error of the Estimate 1 872 a 760 746 5 52134 2 912 b 832 812 4 75122 a Predictors (Constant), A level entry points b Predictors (Constant), A level entry points, hours spent revising ANOVA a Model Sum of Squares df Mean Square F Sig 1 Regression 1735 266 1 1735 266 56 922 000 b Residual 548 734 18 30 485 Total 2284 000 19 2 Regression 1900 241 2 950 121 42 089 000 c Residual 383 759 17 22 574 Total 2284 000 19 a Dependent Variable exam score b Predictors (Constant), A level entry points c Predictors (Constant), A level entry points, hours spent revising Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig B Std Error Beta 1 (Constant) 8 172 9 251 883 389 A level entry points 2 982 395 872 7 545 000 2 (Constant) 3 925 8 114 484 635 A level entry points 1 994 499 583 3 997 001 hours spent revising 476 176 394 2 703 015 a Dependent Variable exam score Excluded Variables a Model Beta In t Sig Partial Correlation Collinearity Statistics Tolerance 1 hours spent revising 394 b 2 703 015 548 465 anxiety 101 b 837 414 199 940 2 anxiety 179 c 1 796 091 410 885 a Dependent Variable exam score b Predictors in the Model (Constant), A level entry points c Predictors in the Model (Constant), A level entry points, hours spent revising

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We want to determine whether hours spent revising, anxiety scores, and A-level entry points have effect on exam scores for participants.

Dependent variable: exam score

Predictors: hours spent revising, anxiety scores, and A-level entry points.

The result of the analysis, COMPUTER output, is provided below.

Answer the following:

Determine the best fitted regression model.
Write the equation of the regression model (best -fit model) and interpret all the Beta coefficients.
Interpret the ANOVA for regression fit.
Determine and interpret the coefficient of determination r².
What can we conclude about the relationship of the dependent and predictor variables?

Regression

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate
1	.872^a	.760	.746	5.52134
2	.912^b	.832	.812	4.75122
a. Predictors: (Constant), A-level entry points
b. Predictors: (Constant), A-level entry points, hours spent revising

ANOVA^a
Model	Sum of Squares	df	Mean Square	F	Sig.
1	Regression	1735.266	1	1735.266	56.922	.000^b
Residual	548.734	18	30.485
Total	2284.000	19
2	Regression	1900.241	2	950.121	42.089	.000^c
Residual	383.759	17	22.574
Total	2284.000	19
a. Dependent Variable: exam score
b. Predictors: (Constant), A-level entry points
c. Predictors: (Constant), A-level entry points, hours spent revising

Coefficients^a
Model	Unstandardized Coefficients	Standardized Coefficients	t	Sig.
B	Std. Error	Beta
1	(Constant)	-8.172	9.251		-.883	.389
A-level entry points	2.982	.395	.872	7.545	.000
2	(Constant)	-3.925	8.114		-.484	.635
A-level entry points	1.994	.499	.583	3.997	.001
hours spent revising	.476	.176	.394	2.703	.015
a. Dependent Variable: exam score

Excluded Variables^a
Model	Beta In	t	Sig.	Partial Correlation	Collinearity Statistics
Tolerance
1	hours spent revising	.394^b	2.703	.015	.548	.465
anxiety	.101^b	.837	.414	.199	.940
2	anxiety	.179^c	1.796	.091	.410	.885
a. Dependent Variable: exam score
b. Predictors in the Model: (Constant), A-level entry points
c. Predictors in the Model: (Constant), A-level entry points, hours spent revising