Explore BrainMass
Share

Explore BrainMass

    Statistics Homework

    This content was COPIED from BrainMass.com - View the original, and get the already-completed solution here!

    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

    © BrainMass Inc. brainmass.com October 10, 2019, 12:16 am ad1c9bdddf
    https://brainmass.com/statistics/probability/anova-regression-calculations-285440

    Attachments

    Solution Summary

    This posting contains the solution to the given problems.

    $2.19