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Analyzing Survey Data

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1. What are the two chief considerations in analyzing survey data?
2. How are statistics used to summarize survey data? Support your answer with examples.

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Survey Data

1. What are the two chief considerations in analyzing survey data?

a) Reliability is the extent to which the survey, experiment or any measuring procedure can produce the same result even after repeated trials. Without the ability to yield consistent results, the research survey data would not be able to conclude, formulate theories or claim that the research work has proven generalizability.

b) Validity refers to the degree of accuracy of the study or research survey data as it assess the specific concept that is being measured. Validity is concerned with the survey's success at what the researcher aims to measure.
Although surveys have the tendency to be weak on validity, ...

Solution Summary

The solution describes the two chief considerations in analyzing survey data, and how statistics are used in summarizing survey data. References are included.

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Regression Analysis for Job Satisfaction Survey Data

Using the data set below complete the following:

TEST #1: Regression Analysis - Benefits & Intrinsic
Perform the following Regression Analysis, using a .05 significance level.
Run a regression analysis using the BENEFITS column of all data points in the AIU 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.
Copy and paste the results of the output to your report in Microsoft Word.
Create a graph with the trendline displayed the 3 regression.
Copy and paste the results of the output to your report in Microsoft Word.

TEST #2: Regression Analysis - Benefits & Extrinsic
Perform the following Regression Analysis, using a .05 significance level.
Run a regression analysis using the BENEFITS column of all data points in the AIU 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.
Copy and paste the results of the output to your report in Microsoft Word.
Create a graph with the trendline displayed for the regression.
Copy and paste the results of the output to your report in Microsoft Word.

TEST #3: Regression Analysis - Benefits & Overall Job Satisfaction
Perform the following Regression Analysis, using a .05 significance level.
Run a regression analysis using the BENEFITS column of all data points in the AIU 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.
Copy and paste the results of the output to your report in Microsoft Word.
Create a graph with the trendline displayed for the regression.
Copy and paste the results of the output to your report in Microsoft Word.

Overview of the Regressions
Complete the table with the following information:
Dependent Variable Slope Y-intercept Equation
Intrinsic

Extrinsic

Overall

State the slope and the y-intercept for the three regressions.
State the least squares regression line equations for the threes regressions.
State the R-squared value for each of the regressions.

Analysis of the Regressions:
Identify at least one similarity and one difference from the regression output or graphs above.
Identify the strongest correlation coefficient between the three outputs above and explain why that is the strongest. Be sure to relate this to the practical application why in the real world sense do you believe these variables have the strongest relationship.
Give a short summary of the above.

Data Set to use for assignment
Gender Age Department Position Tenure Job Satisfaction Intrinsic Extrinsic Benefits
2 1 3 2 3 5.2 5.5 6.8 1.4
1 1 1 1 3 5.5 5.5 5.5 5.4
2 3 1 1 1 4.9 5.2 4.6 6.2
1 1 2 2 1 5.5 5.3 5.7 2.3
1 1 2 1 1 5.2 4.7 5.6 4.5
1 2 2 1 1 5.5 5.5 5.5 5.4
1 3 1 1 1 4.9 5.2 4.6 6.2
1 2 1 1 1 3.9 2.1 5.7 2.3
2 2 2 1 2 5.2 4.7 5.6 4.5
1 2 2 1 2 5.5 5.4 5.6 5.4
1 2 2 2 2 5.9 6.2 5.5 6.2
1 2 1 1 1 4.9 5.2 4.6 6.2
1 3 1 2 2 5.5 5.3 5.7 2.3
2 2 2 1 1 5.2 4.7 5.6 4.5
1 2 2 1 1 5.5 5.4 5.6 5.4
2 2 2 2 3 5.4 6.2 4.6 6.2
1 1 2 2 1 5.5 5.2 5.7 6.2
2 2 2 1 2 5.5 5.3 5.6 5.4
2 3 2 1 2 5.4 5.3 5.5 6.2
2 1 1 1 3 5 5.3 4.6 2.3
1 1 2 1 1 5.2 4.7 5.7 2.3
1 1 2 2 2 5.5 5.3 5.6 4.5
1 3 2 1 1 5.1 4.7 5.5 2.3
1 2 1 2 3 4.9 5.2 4.6 6.2
1 2 1 1 2 5.5 5.3 5.7 2.3
1 3 2 1 2 5.2 4.7 5.6 4.5
1 2 2 1 3 5.5 5.4 5.5 5.4
1 1 3 2 2 5.4 6.2 4.6 6.2
1 2 1 2 1 5.5 5.2 5.7 2.3
1 2 1 2 1 5.5 5.3 5.6 4.5
2 2 2 1 2 5.5 5.4 5.6 5.4
2 3 2 2 2 5.9 6.2 5.5 6.2
2 3 1 1 1 4.9 5.2 4.6 6.2
2 2 2 1 2 5.5 5.3 5.7 2.3
2 2 2 1 2 5.2 4.7 5.6 4.5
2 2 3 2 2 5.5 5.4 5.6 5.4

KEY TO SURVEY

Demographics

Gender
1 Male
2 Female
Age
1 16 - 21
2 22 - 49
3 50 - 65
Department
1 Human Resources
2 Information Technology
Position
1 Hourly Employee (Overtime Eligible)
2 Salaried Employee (No Overtime)
Tenure With Company
1 Less than 2 years
2 2 to 5 years
3 Over 5 Years

Four Survey Measures
SURVEY MEASURE #1 OVERALL JOB SATISFACTION (Scale 1-7)
1 = Least Satisfied
7 = Most Satisfied
SURVEY MEASURE #2 INTRINSIC JOB SATISFACTION (Scale 1-7)
1= Least Satisfied
7= Most Satisfied
SURVEY MEASURE #3 EXTRINSIC JOB SATISFACTION (Scale 1-7)
1 = Least Satisfied
7 = Most Satisfied
SURVEY MEASURE #4 BENEFITS (Scale 1-7)
1= Least Satisfied
7= Most Satisfied

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