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    Regression Analysis: 4 Steps for Benefits and Job Satisfaction

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    First run a regression analysis using the benefits column of all data points in the data set as the independent variable and the intrinsic job satisfaction column of all data points in the AIU data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

    Next, run a regression analysis using the benefits column of all data points in the data set as the independent variable and the extrinsic job satisfaction column of all data points in the AIU data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

    Next, run a regression analysis using the benefits column of all data points in the data set as the independent variable and the overall job satisfaction column of all data points in the AIU data set as the dependent variable. Create a graph with the trendline displayed. What is the least squares regression line equation? What are the slope and the y-intercept? What is the R-squared value?

    Finally, make very specific comments and give reasons regarding any similarities or differences in the output results. Which regression produces the strongest correlation coefficient result? Why?

    These are the key components I am focusing on:
    Run regression with Benefits and Intrinsic - provide Excel output
    Run regression with Benefits and Extrinsic - provide Excel output
    Run regression with Benefits and Overall - provide Excel output
    Graphs with trendlines for all three regressions
    Slopes and y-intercepts for all three regressions
    R-squared values for all three regressions
    Comment on similarities, differences and reasons
    Which regression produces the strongest correlation coefficient and why?

    Attachment(s):Copy of DataSetandDataSetKey_0902B.xls

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    https://brainmass.com/statistics/regression-analysis/regression-analysis-4-steps-for-benefits-and-job-satisfaction-280572

    Solution Preview

    ** Please see the attached file for the complete solution response **

    Job satisfaction survey

    Following is the Regression output obtained using Excel Data Analysis tool for the variables "Benefits" and "Intrinsic job satisfaction".

    SUMMARY OUTPUT

    Regression Statistics
    Multiple R 0.193868
    R Square 0.037585
    Adjusted R ...

    Solution Summary

    This solution provides a detailed explanation of the given regression analysis problem and includes an Excel formatted scatter plot for all three regressions.

    $2.19

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