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Correlation and Regression Analysis Using Sun Coast Data SetUsing the Sun Coast data set, perform a correlation analysis, simple regression analysis, and multiple regression analysis, and interpret the results.Please follow the template (attached) to complete your assignment.You will utilize Microsoft Excel ToolPak for this assignment.Example:Correlation AnalysisRestate the hypotheses.Provide data output results from Excel Toolpak.Interpret the correlation analysis results Simple Regression AnalysisRestate the hypotheses.Provide data output results from Excel Toolpak.Interpret the simple regression analysis results Multiple Regression AnalysisRestate the hypotheses.Provide data output results from Excel Toolpak.Interpret the multiple regression analysis results. The title and reference pages do not count toward the page requirement for this assignment. This assignment should be no less than two pages in length, follow APA-style formatting and guidelines, and use references and citations as necessary.Running head: INSERT TITLE HERE
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Data Analysis: Hypothesis Testing
Use the Sun Coast Remediation data set to conduct a correlation analysis, simple
regression analysis, and multiple regression analysis using the correlation tab, simple regression
tab, and multiple regression tab respectively. The statistical output tables should be cut and
pasted from Excel directly into the final project document. For the regression hypotheses, display
and discuss the predictive regression equations.
Correlation: Hypothesis Testing
Restate the hypotheses:
Example:
Ho1: There is no statistically significant relationship between height and weight.
Ha1: There is a statistically significant relationship between height and weight.
Enter data output results from Excel Toolpak here.
Interpret and explain the correlation analysis results below the Excel output. Your
explanation should include: r, r2, alpha level, p value, and rejection or acceptance of the null
hypothesis and alternative hypothesis.
Example:
The Pearson correlation coefficient of r = .600 indicates a moderately strong positive
correlation. This equates to an r2 of .36, explaining 36% of the variance between the variables.
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Using an alpha of .05, the results indicate a p value of .023 < .05. Therefore, the null hypothesis is rejected, and the alternative hypothesis is accepted that there is a statistically significant relationship between height and weight. Note: Excel data analysis Toolpak does not automatically calculate the p value when using the correlation function. As a workaround, the data should also be run using the regression function. The Multiple R is identical to the Pearson r in simple regression, R Square is shown, and the p value is generated. Be sure to show your results using both the correlation function and simple regression function. Simple Regression: Hypothesis Testing Restate the hypotheses: Ho2: Ha2: Enter data output results from Excel Toolpak here. Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficient, and the regression model as an equation with explanation. Multiple Regression: Hypothesis Testing Restate the hypotheses: Ha3: Ha3: Enter data output results from Excel Toolpak here. Rev. 02.03.2019 INSERT TITLE HERE 4 Interpret and explain the simple regression analysis results below the Excel output. Your explanation should include: multiple R, R square, alpha level, ANOVA F value, accept or reject the null and alternative hypotheses for the model, statistical significance of the x variable coefficients, and the regression model as an equation with explanation. Rev. 02.03.2019 INSERT TITLE HERE 5 References Include references here using hanging indentations. Remember to remove this example. Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Thousand Oaks, CA: Sage. Rev. 02.03.2019 Purchase answer to see full attachment

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