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Research: Levels of Measurement

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Research design is an area where researchers collect various data to address important questions. For example, if researchers wish to find characteristics of people most likely to develop lung cancer, they will have to collect appropriate data first. Investigate 3 different research questions and the appropriate data one needs to collect for each, including the level(s) of the data to be collected for each question. Share with the other students, your research questions and the level(s) of the data to be collected for each. Cite your sources.

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It is essential to be able to identify the levels of data used in a research design. They are directly associated with determining which statistical methods are most appropriate for testing research hypotheses.
-Nominal: Classifies objects by type or characteristic (sex, race, models of vehicles, political jurisdictions)
-Ordinal: classifies objects by type or kind but also has some logical order (military rank, letter grades)
-Interval: classified by type, logical order, but also requires that differences between levels of a category are equal (temperature in degrees Celsius, distance in kilometers, age in years)
Properties:
-Ratio: same as interval but has a true zero starting point (income, education, exam score). Identical to an interval-level scale except ratio level data begin with the option of total absence of the characteristic. For most purposes, we assume interval/ratio are the same.

Why do people develop type 2 diabetes?
Appropriate Data Collection:
-Weight. (Nominal)
Being overweight is a primary risk factor for type 2 diabetes.
The more ...

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ANOVA and Regression Calculations

Case Study of ZYX Incorporated

Case Study of ZYX Incorporated

Executive Summary
The below details is a summary of the research and findings that was completed by Team B Enterprises. This study was conducted with the employees to determine the job satisfaction and stress level of the recently announced move to a new location This will also include the determination of employee morale, address the complaints that were brought to the attention of human resources, discuss turnover rate, sick leave, absenteeism, and job satisfaction. Ultimately, this study will outline the findings of the survey to include the necessary details to move forward with a stepped approach to the make the upcoming move seamless. We developed a questionnaire that measures one's stress level and jobs satisfaction on the following demographic characteristics: occupation, income, education, commute time and gender. This will also include details pertaining to improving the challenges of the organization such as job satisfaction and employee morale to turn the culture of the organization into what the company is all about.
About the company: ZYX is a publicly owed electronics-manufacturing firm. The firm has 1,500 employees and started it's operation is 1965 by it's current president and CEO Bob Imdaman. ZYX went public in 1981 and its stock trades on the NASDAQ.
Phase I: Research Preparation
Problem Statement
The challenge the organization faces the moral of the organization and how the turnover has a direct impact to the bottom line and how the costs of training new individuals are not cost effective. Also, with this future move for the organization, more and more individuals are calling in sick and there is an increase level of absenteeism. The goal is to improve morale, reduce turnover and increase job satisfaction.

Research Questions
RQ1: Which position is feeling the least stress and Job Sat?
RQ2: Which gender is showing less job satisfaction, female or male?
RQ3: Is there a correlation of job satisfaction to education?

Table 1
Variables in the ZYX Case Study
Variable Typical Value Level of Measurement (Attribute/Numeric)
Position Title Attribute
Income < $25k Numeric
Education Bachelors Attribute
Commute < 30 min Numeric
Gender Male, Female Attribute
Job Sat. 56 Numeric
Stress 10 Numeric
Interest 2 (coded) Attribute
Table 2
Research Question Variables
Research Question Independent Variable Dependent Variable
Which position is feeling the least stress and Job Sat? X
Which gender is showing less job satisfaction, female or male? X
Is there a correlation of job satisfaction to education? X

Phase II: Descriptive Analysis
Summary Measure of Attribute Variables
Table 3
Summary Measure of Position
Position Frequency, f Cumulative Frequency, Cf Relative Frequency, Rf Cumulative Rf
Administrative 36 36 0.141176 0.141176
Blue Collar 13 49 0.05098 0.192157
Managerial 52 101 0.203922 0.396078
Professional 128 229 0.50961 0.898039
Other 26 255 0.101961 1
Total 255 670 1 2.627451
Table 4
Summary Measure of Income
Income Frequency, f Cumulative Frequency, Cf Relative Frequency, Rf Cumulative Rf
<$25k 39 79 0.15294 0.15294
$25k - $35k 73 152 0.28627 0.439216
$36k - $45k 71 223 0.27843 0.717647
$46k - $55k 36 259 0.14118 0.858824
$56k - $65k 16 275 0.06275 0.921569
>$65k 20 988 0.07843 1.000000
Total 255 1976 1.00000 4.090196
Table 5
Summary Measure of Education
Education Frequency, f Cumulative Frequency, Cf Relative Frequency, Rf Cumulative Rf
High School 23 23 0.090196 0.090196
AA 85 108 0.333333 0.423529
Bachelors 114 222 0.447059 0.870588
Masters 28 250 0.109804 0.980392
Doctorate 5 255 0.019608 1
Total 255 858 1 3.27451
Table 6
Summary Measure of Commute Time
Commute Time Frequency, f Cumulative Frequency, Cf Relative Frequency, Rf Cumulative Rf
<30 min 175 175 0.589226 0.589226
30 min - 1 Hr 80 80 0.26936 0.858586
1.1 - 2 Hrs 25 280 0.084175 0.942761
2.1 - 3 Hrs 17 297 0.57239 1
Total 297 832 1 2.801347
Table 7
Summary Measure of Gender
Gender Frequency, f Cumulative Frequency, Cf Relative Frequency, Rf Cumulative Rf
Female 116 116 0.454902 0.454902
Male 139 255 0.545098 1
Total 255 371 1 1.454902
Table 8
Summary Measure of Interest
Interest Frequency, f Cumulative Frequency, Cf Relative Frequency, Rf Cumulative Rf
1 Strongly Agree 79 79 0.262485 0.262485
2 Agree 77 156 0.255814 0.518272
3 No Opinion 31 187 0.10299 0.621262
4 Disagree 35 222 0.116279 0.737542
5 Str. Disagree 79 301 0.262458 1
Total 301 945 1 2.877076
Summary Measure of Numeric Variables
Table 9
Summary Measure of Job Satisfaction
Central Tendency
n Mean Median Mode
255 62.20 63 61.00
Dispersion
Std Dev Variance Range Min/Max

11.96 143 70 19/89

Table 10
Summary Measure of Stress
Central Tendency
n Mean Median Mode
255 25.67 20.00 10
Dispersion
Std Dev Variance Range Min/Max
22.74 517.27 120 0/120
Histograms of Job Satisfaction and Stress
Job satisfaction see appendix A.
Work related Stress see appendix B

Findings (what does this mean)

Phase III: Chi-Square
Relationship Between Respondent's Interest and Demographics
Analysis Unit One employee
Sample Size
Target Population
Research Question
Chi-Square Findings (See Appendix B for details)
Chi-Square Position Income Education Commute Gender
Hypothesis Ho:
H1:
Significance Level 0.05 0.05 0.05 0.05 0.05
Test statistic Χ2
p-Value
Decision
Analysis

Phase IV: ANOVA
Relationship Between Stress Level and Demographics
Analysis Unit
Sample Size
Target Population
Research Question

ANOVA Findings (See Appendix C for details)
ANOVA Position Income Education Commute Gender
Hypothesis Ho:
H1:
Significance Level 0.05 0.05 0.05 0.05 0.05
p-Value
Decision
Analysis
Phase V: Regression Analysis
Relationship Between Respondent's Job Satisfaction and Stress
Analysis Unit
Sample Size
Target Population
Research Question
Regression Findings (See Appendix D for details)
Regression
r
R2
Hypothesis Ho:
H1:
Significance Level 0.05
p-Value
Decision
Analysis

a. Describe the relationship between Job Satisfaction and Stress.

b. Can you mathematically predict an employee's job satisfaction based on their stress level (Give an illustration, assuming that an employee has a stress level of 20.)?

c. How Reliable is this prediction (consider, P-value, r and R-squared)?

Appendix A

Descriptive statistics For Job Sat

JobSat
count 255
mean 62.20
sample variance 143.00

sample standard deviation 11.96
minimum 19
maximum 89
range 70

1st quartile 55.50
median 63.00
3rd quartile 71.00
interquartile range 15.50
mode 61.00

low extremes 0
low outliers 4
high outliers 0
high extremes 0

Frequency Distribution - Quantitative - Job Sat

JobSat cumulative
lower upper midpoint width frequency percent frequency percent
10 < 20 15 10 1 0.4 1 0.4
20 < 30 25 10 1 0.4 2 0.8
30 < 40 35 10 10 3.9 12 4.7
40 < 50 45 10 28 11.0 40 15.7
50 < 60 55 10 60 23.5 100 39.2
60 < 70 65 10 78 30.6 178 69.8
70 < 80 75 10 63 24.7 241 94.5
80 < 90 85 10 14 5.5 255 100.0

255 100.0

Appendix b

Descriptive statistics For Stress

Stress
count 255
mean 25.67
sample variance 517.27
sample standard deviation 22.74
minimum 0
maximum 120
range 120

1st quartile 10.00
median 20.00
3rd quartile 35.00
interquartile range 25.00
mode 10.00

low extremes 0
low outliers 0
high outliers 12
high extremes 1

Frequency Distribution - Quantitative - Stress

Stress cumulative
lower upper midpoint width frequency percent frequency percent
0 < 10 5 10 50 19.6 50 19.6
10 < 20 15 10 62 24.3 112 43.9
20 < 30 25 10 56 22.0 168 65.9
30 < 40 35 10 28 11.0 196 76.9
40 < 50 45 10 20 7.8 216 84.7
50 < 60 55 10 15 5.9 231 90.6
60 < 70 65 10 9 3.5 240 94.1
70 < 80 75 10 2 0.8 242 94.9
80 < 90 85 10 7 2.7 249 97.6
90 < 100 95 10 3 1.2 252 98.8
100 < 110 105 10 1 0.4 253 99.2
110 < 120 115 10 1 0.4 254 99.6
120 < 130 125 10 1 0.4 255 100.0

255 100.0

References
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2005). Statistical techniques in business and economics (12th ed.). New York: McGraw-Hill.

Appendix A
Chart A1
Histogram of Job Satisfaction & Stress

Appendix B
Chi-Square Calculations

Appendix C
ANOVA Calculations

Appendix D
Regression Calculations

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