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Discussion about a simple regression


Discussion:

1. Work through a simple regression calculation using intrinsic job satisfaction and extrinsic job satisfaction. You may USE DataSet file in  or you may select a group of 30 data points. You must provide the 30 data points that you used however or I will be unable to check your work and you will lose points, possibly all points for part 3. You are welcome to decide which group you want to make the dependent variable and which the independent variable. State this choice clearly. Show your regression output.

2. The final answer will then be a complete model equation resembling: Y = bx + a (provide work to support your answer).

3. Comment on the model equation and the summary regression output in terms of the correlation of these two variables.

4. Work through a second simple regression by switching the dependent and independent variables used in the first regression. Show your regression output.

5. Make very specific comments and give reasons regarding any similarities or differences in Multiple R and the ANOVA coefficients.

KEY TO JOB SATISFACTION SURVEY
 
Gender   Tenure With Company  
1 Male 1 Less than 2 years
2 Female 2 2 to 5 years
Age   3 Over 5 Years
1 21 and under    
2 22-49 OVERALL Scale from 1-7
3 50 and over JOB SATISFACTION 1= Least Satisfied
Department      7= Most Satisfied
1 Human Resources    
2 Information Technology INTRINSIC Scale from 1-7
3 Administration JOB SATISFACTION 1= Least Satisfied
      7= Most Satisfied
Position      
1 Hourly Employee (Overtime Eligible) EXTRINSIC Scale from 1-7
2 Salaried Employee (No Overtime) JOB SATISFACTION 1= Least Satisfied
      7= Most Satisfied
 

GENDER AGE DEPT POSITION TENURE OVERALL INTRINSIC EXTRINSIC
2 2 3 2 3 6.2 6.33 7
1 1 1 1 2 4.6 3.83 6.5
1 2 3 1 1 2.4 5.33 6
2 2 3 2 1 5.8 6.17 3
1 2 3 2 1 2.8 5.33 3
1 1 2 1 2 2.6 5.33 4
2 1 3 1 2 3.8 4 5
1 2 3 1 1 6.6 6.17 2.5
1 3 3 2 2 7 5 6
1 3 3 2 3 5.4 6.33 5.5
2 2 3 2 1 5.6 5.2 6
1 1 1 1 2 5 6.17 5.5
2 2 2 2 2 4 5.17 4
2 2 3 1 1 3.6 6.67 6
2 2 3 1 2 4.8 4.17 6
1 1 2 2 2 4 5.17 5
2 2 2 1 1 4 4.67 4
1 2 3 2 1 1.6 2.67 4
2 3 2 1 2 6.6 5 6.5
2 1 1 2 2 4.6 4.25 5
2 2 3 2 1 1.6 5.17 4
2 2 3 1 1 2.8 6.17 6
2 2 2 1 2 3.6 6.5 4
2 2 3 2 2 2 3.67 1.5
1 2 3 1 1 6.8 6.83 6
1 2 2 1 2 5 4.83 5
2 2 3 2 2 2.6 6 2
1 2 3 1 1 6.4 4.5 6
2 1 2 1 1 4.2 6 6
2 2 2 2 1 5.4 3.17 5
1 2 3 2 1 4.4 5 7
1 2 3 1 1 5 4.17 6
2 2 2 1 1 3.8 4.33 4
2 2 2 1 3 3.2 5.17 1
2 2 3 1 1 5 5 4
1 2 3 1 1 7 7 7
2 3 2 2 1 4 5.5 6
1 2 3 1 2 6.8 7 5.5
2 2 2 2 3 3.8 5.33 6
2 2 2 1 1 4.6 4.33 6
2 2 3 1 3 3.2 4.67 4
2 2 2 1 2 2 3.67 6
1 2 3 1 1 6.2 5.67 7
1 2 3 1 2 4.6 5.17 6
2 2 3 1 1 4.8 5.5 6
2 2 3 2 3 5.4 6.17 5.5
1 2 3 1 2 5 5 5
1 2 3 1 1 4.2 5.83 6
1 3 3 1 3 4.6 4.67 4
1 3 2 2 1 3.2 3.83 4
2 2 3 2 3 4 6.17 5
2 2 3 2 1 3.8 6.17 5
2 3 3 2 1 4.2 4.5 6
2 2 2 2 3 5.6 6 5
2 2 3 1 3 5.6 5.83 6
1 2 3 1 1 7 6.83 7
2 2 3 1 1 4.6 5 6
2 3 2 2 1 2 5.83 2
1 3 3 1 1 2.8 5.67 1.5
1 2 3 1 1 3 4.33 5.5
2 2 2 2 1 3 5.24 6
1 1 2 1 2 4.6 5.67 2
2 2 2 1 2 4.6 5 4
2 2 3 1 1 5.4 5.67 7
2 2 2 1 1 5.2 6.17 2
1 2 3 1 1 4 4.67 6
1 2 3 1 1 5.2 5.17 2
2 2 3 2 1 4.8 5 2
1 2 3 2 1 3.4 7 6
1 3 3 2 1 3.4 4.5 6
1 3 3 1 1 3.6 5.17 6
1 3 3 2 1 4 5.5 6
1 2 2 1 1 1.8 3 3
2 3 2 2 2 4.8 5 6
1 2 2 1 3 3.6 4.83 2.5
2 2 2 1 1 4.2 5 6
2 1 2 1 1 4.8 4.5 5.5
1 2 2 1 1 5.4 4.67 6
2 2 3 1 3 4 4.17 6.5
1 2 3 1 1 4.8 5.5 4.5
1 2 3 2 3 4.4 3.33 6
2 1 3 1 2 4.8 5.17 4
1 3 3 2 1 2 5 6
1 2 3 1 1 4.8 5 6
2 2 2 1 1 4.6 6.33 6.5
2 3 3 2 1 3.8 6.33 5.5
1 2 3 2 1 6.6 7 5.5
2 2 3 1 2 3.6 6.67 6
1 2 2 2 3 2.6 3.83 3
2 2 2 1 1 5.4 5.67 4
1 3 3 1 1 3.2 5 6
2 2 3 2 3 2.4 5.33 3.5
2 2 3 1 2 4.6 4.75 5.5
2 3 2 1 1 4.6 4.5 3
2 2 3 2 3 4.2 4.83 4
1 3 3 2 1 4.6 4.33 5.5
2 2 2 1 1 3.2 6.5 5.5
2 2 2 2 2 4.2 6 7
2 2 3 2 3 4.4 5.5 7
2 2 2 2 3 3.4 6.17 6
1 2 2 1 2 3.2 4.83 6
2 2 2 2 1 4.6 6.33 7
1 2 3 1 1 5 4.83 6
2 2 2 2 1 2.8 4.33 5.5
2 2 3 1 1 3.8 5 1
2 3 2 1 3 3.8 2 1.5
2 2 2 1 1 1 2 1
2 1 1 2 2 3.8 5 6
2 1 2 2 1 5.6 6.83 7
1 3 2 2 2 6 6.33 6.5
1 2 3 1 2 2.2 4 2.5
1 2 3 1 1 3.4 4.5 4
2 2 2 1 1 4.2 7 5.5
1 2 2 2 2 4 4.67 6
2 2 3 2 1 4.2 3.5 1.5
2 2 3 1 1 6 6.67 3
1 2 3 1 1 3.4 5.33 2
2 1 3 1 2 3.6 4.83 4
2 2 3 2 1 3.8 4.83 4
1 2 3 2 1 6.6 6.83 6
2 3 3 2 1 3.8 4.83 7
2 1 2 2 2 4 4.5 1.5
1 2 3 1 1 5.2 5 6
2 2 3 2 1 1 5.17 1
2 2 3 2 2 6.2 7 7
1 2 3 2 1 7 6.83 6
2 2 2 1 3 5 3.5 5
1 2 2 1 1 7 6.5 6
2 2 2 2 3 5.2 5 6
2 1 2 2 2 2 5.17 1.5
2 1 2 2 2 2.8 4.5 6
2 2 2 1 1 5.6 5.33 5
1 2 3 1 1 2.6 4.5 4
1 2 3 2 1 3.2 4.33 2.5
2 1 1 1 1 6 6.67 6
2 2 3 2 1 3.4 5.5 6
2 2 2 2 2 2 4.5 7
1 2 3 1 1 6.6 5.17 5.5
2 2 3 2 1 6.2 4.83 4.5
1 3 3 2 1 5 5 2
1 1 2 2 1 2.6 4 5
2 2 2 2 2 5 5.17 6
1 1 3 1 2 5.6 5.67 6
1 2 3 2 1 4.4 5.67 6
2 1 1 1 2 3.6 5 4.5
1 1 1 1 2 2.2 4.17 4.5
1 2 3 1 2 7 7 7
1 2 3 2 1 1.8 4.33 3
1 3 3 2 1 3.6 4.17 6
1 2 3 1 1 4 5.17 2
2 1 1 1 2 6.2 6.33 5.5
1 2 2 1 3 5.8 5.83 5
1 2 3 1 1 4.6 6.17 3
2 2 3 1 1 4 4.67 4
1 2 3 1 1 5.8 6.17 7
2 2 2 1 1 5.4 4.83 6.5
2 1 2 2 3 3 3.67 4
2 2 3 2 1 5.8 5.67 7
2 2 3 2 1 3.2 5.33 1.5
1 1 2 1 1 2 4.67 2.5
1 3 3 1 1 4.6 5 6
1 1 3 2 1 4 5.33 6.5
1 2 3 1 1 3.4 4.67 6
2 3 3 2 1 3.4 6.33 4
2 3 3 2 3 4.4 5.3 5
2 2 3 1 3 6 7 3
1 3 3 1 3 5.2 5.67 5.5
2 2 3 2 3 6 6.83 6
1 3 3 2 3 5.6 5.83 6
2 3 2 2 3 7 7 1.5
1 3 3 1 3 1.8 5.33 5.5
2 1 1 2 2 4 3.5 3
2 2 3 1 1 3.8 5.5 4
2 2 3 2 2 5 3.17 4.5
2 2 3 2 1 3.2 5.33 4.5
1 2 3 1 1 2.6 5.67 6
2 3 3 2 1 2 5.67 6
2 2 2 2 2 3.6 5.33 3
1 2 2 2 1 5.6 5.67 4.5
1 2 3 1 1 4.8 4.33 6
2 2 3 2 3 5.4 5 6.5
2 2 3 1 1 6 5 7
2 2 3 1 1 4.4 5.33 4.5
1 1 3 1 1 4.2 4.17 5
2 2 3 1 1 4.6 5.33 6.5
2 1 3 1 1 4.2 5.67 4
2 2 3 1 1 5.8 6.33 6
1 1 2 1 2 3 4.67 6
2 2 2 1 1 2.2 1 1
1 3 3 1 3 5.2 4.33 4
2 2 3 1 2 1 4.67 5
1 2 3 2 1 4 4.5 6
1 2 3 2 3 2.2 6.17 1.5
2 2 3 1 1 6 6.67 5
2 2 2 1 1 5.6 6.33 6
2 2 3 2 1 5 7 2.5
2 2 2 2 3 4.8 4.67 4
1 3 2 1 1 6.2 4.83 4
2 3 2 1 3 1 5 1
2 2 3 1 1 5 5 7
2 2 3 1 1 4.4 6.5 5.2
2 2 3 2 2 5.6 5.83 5
2 1 2 2 1 5 5.17 4
1 3 3 1 1 4 5.5 6
2 2 2 1 1 4.6 5.33 3
1 1 3 1 2 5.8 7 5.5
2 3 3 1 3 2.4 4.33 6
1 1 2 2 3 3.8 3.83 3
2 2 2 2 3 4.2 4.67 3
2 1 3 1 1 3.8 6 6
1 2 3 2 1 4.8 4.33 6.5
1 2 3 2 1 3 5 6
1 2 3 1 1 4.8 6.33 6.5
1 1 3 1 2 2.8 5.5 5.5
2 1 3 1 1 5.4 5.33 6
2 2 3 2 3 3.2 3 6
2 1 3 1 1 6.2 6.33 6
2 2 3 1 2 6.2 5.67 2
1 2 3 1 2 7 6.5 6
2 2 3 1 1 5.6 6.17 6
1 3 3 1 1 4.6 5 6
1 2 3 1 1 4.6 4.5 4.5
1 2 3 2 1 2.8 5 1
2 2 2 2 2 4.4 3.5 4.5
2 2 2 1 1 5.8 4.17 5
2 2 2 1 1 4.6 5.17 3
1 2 2 2 1 4.8 5 7
2 2 1 1 1 4.2 7 5.5
1 3 2 2 2 5.2 6 5.2
2 1 2 1 1 2.2 5.17 5.5
2 1 2 2 1 6 5.33 7
2 2 3 1 3 3.4 4.5 6
2 2 2 2 1 3.8 5.17 6
2 1 2 2 2 3.6 6 7
2 2 3 2 1 5.4 4.5 7
2 2 3 2 1 4.2 6.33 6
1 2 3 1 1 5.2 5.33 5.5
2 2 2 1 1 4 6.33 2.5
2 2 2 1 1 5.8 7 6
2 1 2 2 1 1.8 3 4
2 2 2 2 1 2 7 6
1 1 2 1 2 3.6 4.17 4.5
2 2 3 1 2 4.6 4.17 6.5
2 2 2 2 1 3.2 5.17 5.5
1 2 2 2 1 5.8 4.67 5
1 3 2 2 1 2.6 5 1
2 1 2 2 2 4.8 6.83 6
2 2 2 2 2 4 4.5 4
2 2 2 2 2 3.6 4.17 2
2 2 3 1 3 5.8 5 6
1 2 3 2 3 1.8 5.33 6
1 3 3 1 1 5 6.17 7
2 2 3 2 2 1.8 4 1
2 2 3 1 1 6.2 7 5.5
2 2 3 2 1 2 5.33 1.5
1 1 3 1 1 4.6 5 3.5
1 3 3 2 1 6 6.17 6.5
2 2 3 1 3 6.2 5.67 4
2 2 3 1 3 5.8 5.83 6
1 3 3 2 1 3.4 6.17 5.5
1 3 3 1 1 6.2 5 6
1 1 2 1 2 1.6 5.67 5
2 1 3 2 1 5.8 5.83 3.5
1 2 3 2 1 4.6 4.5 5.5
2 2 2 1 1 5.8 6 5
2 2 3 1 1 3.6 5 4.5
2 3 2 2 3 4.4 4.17 3.5
2 2 3 2 3 5.8 5.5 6
2 2 1 2 3 4 4.17 4
1 2 3 1 3 5.4 5 6
2 1 2 1 2 5 5.33 5.5
1 2 3 1 1 4 4.33 6
2 2 3 1 1 2.8 4.5 1
1 1 3 1 1 5.5 5 6
1 3 3 2 1 5.2 4.67 6
1 2 2 1 2 3.8 5 5.5
2 1 3 1 1 5 6.17 7
2 2 2 1 2 4.2 4.83 4.5
2 2 2 2 1 4.8 6.33 5
2 2 3 1 1 4 5 7
1 2 2 1 1 4.6 3.67 6
1 2 3 1 3 5.2 6.33 6
2 2 3 1 2 2 4.83 6.5
1 2 2 1 2 6 6.17 1
2 2 3 1 1 4 3.67 7
2 2 3 2 2 4.6 6.5 5.5
2 2 3 1 3 3 3.67 5
1 3 3 1 1 5.4 5.67 6.5

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Applied Statistics: Discussion about a simple regression
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