Question

Overview of the Study: The data are based on a Comprehensive School Reform (CSR) Initiative that focused on the improvement of reading and writing for students in the primary grade. The school received a grant from the state which was used to strengthen classroom teachers’ instructional skills. The regression outputs present information for students in the school.

Description of the variables: Please use the following description/coding to help you in your analyses.

Gender: female; 1 male=0

Coding – Gender female 1; male=0

In this multiple regression model, the dependent variable is Writing Vocabulary, and the predictor is Gender female 1; male=0

The R² in this model equals .117, which indicates that 11.7% of variance in Writing Vocabulary is explained by the predictors: Gender

This multiple regression model is also statically significant. F (1,44) =, 5.848=P= .020;

Looking at predictors in the model, one can see the is a significant predictor is a statistically significant predictor of; Beta= -.343, t=-2.418, p=.020;

This positive data shows that as Writing vocabulary

For every unit change in the. For every unit change in the.

I’m lost on hot to write the coefficient model and how to write it.

Variables Entered/Removedb
Model		Variables Entered	Variables Removed	Method
dimension0	1	Gendera	.	Enter
a. All requested variables entered.
b. Dependent Variable: Writing Vocabulary

Model Summary
Model		R	R Square	Adjusted R Square	Std. Error of the Estimate
dimension0	1	.343a	.117	.097	14.145
a. Predictors: (Constant), Gender

ANOVAb
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	1170.087	1	1170.087	5.848	.020a
	Residual	8803.391	44	200.077
	Total	9973.478	45
a. Predictors: (Constant), Gender
b. Dependent Variable: Writing Vocabulary

Coefficientsa
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.
		B	Std. Error	Beta
1	(Constant)	26.565	2.949		9.007	.000
	Gender	-10.087	4.171	-.343	-2.418	.020
a. Dependent Variable: Writing Vocabulary

Answer 1