Conduct a Pearson correlation analysis

Assignment Help Applied Statistics

Reference no: EM132286503

Assignment Problems -

Please use the attached data file (Muijs, 2011) to see if you can produce the following SPSS output that aligns with the two prompts.

Problem 1 - Conduct a Pearson's correlation (2-tailed) analysis to assess whether there is a significant correlation between school geometry and school physical education grades.

Correlations
		school grades geometry	school grades physical education
school grades geometry	Pearson Correlation	1	.460**
	Sig. (2-tailed)		.000
	N	575	575
school grades physical education	Pearson Correlation	.460**	1
	Sig. (2-tailed)	.000
	N	575	588
**. Correlation is significant at the 0.01 level (2-tralied).

Problem 2 - Conduct a Spearman's correlation (2-tailed) analysis to assess whether there is a significant correlation between the variables teachers think that I am good at science and teachers think that I am good at sports.

Nonparametric Correlations - DataSet1

Correlations
			teachers think that I'm good at sports	teachers think that I'm good at science
Spearman's rho	teachers think that I'm good at sports	Pearson Correlation	1.000	.959**
		Sig. (2-tailed)	.	.000
		N	884	884
	teachers think that I'm good at science	Pearson Correlation	.959**	1.000
		Sig. (2-tailed)	.000	.
		N	884	884
**. Correlation is significant at the 0.01 level (2-tralied).

Problem 3 - Conduct a simple linear regression analysis to assess whether age in months predicts school art grades.

Model Summary^b
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	R Square Change	Change Statistics				Durbin-Watson
						F Change	df1	df2	Sig. F Change
1	.289^a	.083	.082	9.78312	.083	51.959	1	571	.000	1.027

a. Predictors: (Constant), age in months

b. Dependent Variable: school grades art

ANOVA^a
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	4972.926	1	4972.926	51.959	.000^b
	Residual	54650.133	571	95.710
	Total	59623.059	572

a. Dependent Variable: school grades art

b. Predictors: (Constant), age in months

Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients Beta	t	Sig.	Collinearity Statistics
Model		B	Std. Error	Standardized Coefficients Beta	t	Sig.	Tolerance	VIF
1	(Constant)	145.944	9.358		15.595	.000
1	age in months	-.536	.074	-.289	-7.208	.000	1.000	1.000

a. Dependent Variable: school grades art

Attachment:- Assignment Files.rar

Reference no: EM132286503

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4/17/2019 9:48:49 PM

Instructions: Please use the attached data file (Muijs, 2011) to see if you can produce the following SPSS output that aligns with the two prompts. APA format as per attached example Please provide an analysis of what the results reveal to you.

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