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Unit 5 – Regression Analysis

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Unit 5 – Regression Analysis

American InterContinental University

When comparing intrinsic, extrinsic, and overall job satisfaction to which will benefits employees more and have a better result with the satisfaction between the company and the employees to become a successful team. All calculation would be on Excel to determine the regression analysis and graphs the correlation between the all three

Introduction When company needs to determine what will work with having happier employees, companies’ uses correlation statistics to help determine which variable value works best. Correlations can be either positive variable value or negative variable value. Using charts and analysis can be useful to determine the results. Regression analysis shows the strengths and weakness of different variables and can help making a decision on which is the strongest variable.
Benefits and Intrinsic Job Satisfaction
Regression output from Excel

Benefits and Extrinsic Job Satisfaction
Regression output from Excel

Benefits and Overall Job Satisfaction
Regression output from Excel
Graph [pic]
Key components of the regression analysis Complete the following chart to identify key components of each regression output.
|Dependent Variable |Slope |Y-intercept |Equation |[pic] |
|Intrinsic |0.056 |5.505 |Y=0.56x5.505 |0.004 |
|Extrinsic |0.151 |4.449 |Y=0.151x=4.449 |0.027 |
|Overall |-0.082 |5.166 |Y=82x=5.166 |0.008 |

Similarities and Differences
One of the similarity that I found between the graphs is between benefits vs intrinsic and benefits vs overall. Both graphs have a negative correlation based in the tread lines. As the value variable x increase the value variable y decreases (Editorial Board, 2012). The extrinsic vs benefits were different from the other two graphs. The correlation was positive as the value of x increase the y increased too. All three shown a weak correlation because the majority of the points weren’t able to form a straight line.
Correlation coefficients
Of all the three outputs the strongest correlation was extrinsic vs benefits, since the value was the closest to 1(Editorial Board, 2012). Meaning with the benefits to the employees will have effect on the extrinsic satisfaction of the employees. Managers can determine if the benefits are actually causing the increase extrinsic job satisfaction by doing a research on the satisfaction. By the company knowing that the job satisfaction is high levels meaning that the employees are happy and the company can have more profits and be successful.
In conclusion, the regression analysis is an important tool when making a determination if there is a statistical relationship between two different variables of interest. Also to see how strong is the relationship between the two variables. Analyzing these three different output the extrinsic vs benefit was the strongest of the correlation relationship.

Editorial Board (2012). Elementary statistics. Schaumburg, IL: Words Of Wisdom.

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