Job Sat. INTR. EXTR. Benefits

5.2 5.5 6.8 1.4
5.1 5.5 5.5 5.4
5.8 5.2 4.6 6.2
5.5 5.3 5.7 2.3
3.2 4.7 5.6 4.5
5.2 5.5 5.5 5.4
5.1 5.2 4.6 6.2
5.8 5.3 5.7 2.3
5.3 4.7 5.6 4.5
5.9 5.4 5.6 5.4
3.7 6.2 5.5 6.2
5.5 5.2 4.6 6.2
5.8 5.3 5.7 2.3
5.3 4.7 5.6 4.5
5.9 5.4 5.6 5.4
3.7 6.2 5.5 6.2
5.5 5.2 4.6 6.2
5.2 5.5 5.5 5.4
5.1 5.2 4.6 6.2
5.8 5.3 5.7 2.3
5.3 4.7 5.6 4.5
5.9 5.4 5.6 5.4
3.7 6.2 5.5 6.2
5.5 5.2 4.6 6.2
5.6 5.6 4.8 5.1

1. 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 data set as the dependent variable.

2. 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 data set as the dependent variable.

3. 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 data set as the dependent variable.

4. Then answer the following questions:
* What are the least squares regression line equations for each of the 3 different regressions?
* What are the slopes and the y-intercepts?
* What are the R-squared values for the 3 different regressions?

5. Finally, make very specific comments and give reasons regarding any similarities or differences in the output results.

6. Which regression produces the strongest correlation coefficient result? Why?

How would you like us to help you with this assignment?

I don't know how to do ANY OF IT. I'm so lost

To answer the questions, we need to perform regression analysis on the given data. Here's how you can do it:

1. First, separate the given data into three columns labeled "INTR." (for intrinsic job satisfaction), "EXTR." (for extrinsic job satisfaction), and "Benefits" (for benefits).

2. To find the least squares regression line equation for the first regression, you need to use the "INTR." column as the dependent variable (y) and the "Benefits" column as the independent variable (x). Plug these values into a regression calculator or use statistical software to obtain the equation: y = mx + b.

3. Repeat the same process for the second regression using the "EXTR." column as the dependent variable (y) and the "Benefits" column as the independent variable (x).

4. Lastly, perform the third regression using the "OVERALL" column as the dependent variable (y) and the "Benefits" column as the independent variable (x).

5. After obtaining the equations for each regression, you can determine the slopes and y-intercepts. The slope (m) represents the change in the dependent variable for each unit change in the independent variable, while the y-intercept (b) represents the value of the dependent variable when the independent variable is zero.

6. To calculate the R-squared values for each regression, you will need to find the coefficient of determination. This value represents the proportion of the dependent variable's variance explained by the independent variable. It ranges from 0 to 1, with 1 indicating a perfect fit.

7. Compare the R-squared values of each regression to determine the strength of the correlation coefficient for each regression. The regression with the highest R-squared value indicates the strongest correlation between the independent and dependent variables.

8. Finally, analyze the results and make specific comments based on the output. Look for similarities or differences in the equations, slopes, y-intercepts, and R-squared values. Discuss any patterns or relationships you observe between benefits and job satisfaction.

By following these steps, you should be able to find the answers to the questions and draw conclusions about the strength and relationship between benefits and job satisfaction variables.

You need more help than we can possibly give.

First, go back and study your text materials again and again. Take notes. Pay particular attention to the examples given. If you're still lost, contact your instructor for additional help.