This report analyses a random sample of 450 staffs from Cuteen factory to study the factors like working hours, job satisfaction, and progress in career. The report includes analysis of working hours, proportion of workers, gender-wise working hours, influence, and correlation coefficient matrix.
Contribute Materials
Your contribution can guide someone’s learning journey. Share your
documents today.
Running head: STATISTICS Statistics Name of the Student: Name of the University: Author’s Note:
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
2STATISTICS Table of Tables Table 1: Table of Working hours...............................................................................................6 Table 2: Table of estimating the proportion of estimation.........................................................7 Table 3: Frequency distribution of gender wise working hours................................................8 Table 4: Frequency distribution of the variable “Influence”.....................................................8 Table 5: Correlation coefficient matrix....................................................................................12 Table of Figures Figure 1: Distribution of Working hours...................................................................................7 Figure 2: Distribution of Working hours...................................................................................8 Figure 3: Frequency distribution about staying in the organization..........................................8 Figure 4: Frequency distribution of gender wise average working hours..................................9 Figure 5: Table of percentage frequencies of types of “Influence”.........................................10 Figure 6: Table of frequencies of types of “Influence”............................................................10 Figure 7: Scatter plot of “Weekly working hours” as dependent and “Age” as independent variable.....................................................................................................................................11 Figure 8: Scatter plot of “Weekly working hours” as dependent and “Educational Years” as independent variable................................................................................................................11 Figure 9: Scatter plot of “Weekly working hours” as dependent and “Salary” as independent variable.....................................................................................................................................11 Figure 10: Scatter plot of “Weekly working hours” as dependent and “Working Years” as independent variable................................................................................................................12 Figure 11: Scatter plot of “Weekly working hours” as dependent and “AtCuteen” as independent variable................................................................................................................12 Figure 12: Scatter plot of “Weekly working hours” as dependent and “NumPromo” as independent variable................................................................................................................13
3STATISTICS To: Lee Maston, Human Resources Manager From: John Frank, Senior Analyst Regarding: Further Analysis of dataset In “Cuteen”, a factory that manufactures car parts of America, the authority wished to study a full-time workforce by enhancing the background of an employee that measures the factors like salary, job satisfaction and progress in career. The report analyses the random sample of 450 staffs that are surveyed with the company internet mail. Various types of variables, factors, association among variables and the comparative study are executed in the following report to represent the overall scenario of the company. Answer 1. The average working hours of all the 450 samples is 45.27 hours. Many workers prefer to work 40 hours per week. The middle most value of working hours is 40 hours. A worker works maximum 89 hours and minimum 28 hours weekly. The estimated working hours per week lies in the interval of 46.18 hours and 44.36 hours. The workers who work weekly more than 68 hours per week are considered outliers of this class. A significant number of workers (214) work weekly 37 hours to 41.5 hours. 50% of the workers work weekly more than 40 hours and less than 50 hours. Answer 2. Out of 450 sampled workers, 80 workers prefer very likely to stay in the organisation. The proportion of such workers is 0.17778. The estimated proportion of sampled workers lies in the proportional range of 0.2131 and 0.14245 (Chen 20111). Therefore, it is 95% evident that the proportion of workers who are likely to stay in the organisation are in the interval of 14% to 21%. Answer 3. The average working hours for 260 male workers is 47.81 hours and for 190 female workers is 41.80 hours (Mendenhall and Sincich 2016). The minimum and maximum working hours of the males is higher than females. Therefore, males are found to be more
Paraphrase This Document
Need a fresh take? Get an instant paraphrase of this document with our AI Paraphraser
4STATISTICS hard-worker than males. Males provide more dedication towards their work with working more in the company. Answer 4. It could be interpreted visualising the frequencies with respect to the types of “Influence”, that 152 (34%) workers feel their ability to influence work decisions. 181 (40%) workersrealizetheircapabilitytoinfluencetheirworkdecisionsmuchofthetime. Comparatively, lesser frequencies are observed as the workers feel their ability sometimes (66) (15%). Least number of people (51, 11%) never feels the influence of work decisions in their work (Neyeloff, Fuchs and Moreira 2012). Answer 5. Positive association indicates that with the higher values of independent variables, the value of response variable increases. Simultaneously, with the lower values of independent variables, the dependent variable decreases (Grégoire 2014). “Age” factor has very week but negative correlation with working hours. “Salary” factor has weak but positive association with weekly working hours (Sedgwick 2012). No other factor has significant association with the working hours (Panik 2012). Uncorrelated factorsare“EducationalYears”,“WorkYears”,ratingof“AtCutten”andratingof “NumPromo”. These factors have no linear significant link with dependent factor “Weekly working hours”. Hence, no change (increase or decrease) in the values of these uncorrelated factors can significantly influence the same dependent factor weekly working hours. Regards. John Frank.
5STATISTICS References: Chen, Z., 2011. Is the weighted z‐test the best method for combining probabilities from independent tests?.Journal of evolutionary biology,24(4), pp.926-930. Grégoire, G., 2014. Multiple linear regression.European Astronomical Society Publications Series,66, pp.45-72. Mendenhall, W.M. and Sincich, T.L., 2016.Statistics for Engineering and the Sciences. Chapman and Hall/CRC. Neyeloff, J.L., Fuchs, S.C. and Moreira, L.B., 2012. Meta-analyses and Forest plots using a microsoft excel spreadsheet: step-by-step guide focusing on descriptive data analysis.BMC research notes,5(1), p.52. Panik, M.J., 2012. Testing Statistical Hypotheses.Statistical Inference: A Short Course, pp.184-216. Sedgwick, P., 2012. Pearson's correlation coefficient.BMJ: British Medical Journal (Online), 345.
6STATISTICS Appendix: Table1: Table of Working hours Figure1: Distribution of Working hours
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.
7STATISTICS Figure2: Distribution of Working hours Table2: Table of estimating the proportion of estimation Figure3: Frequency distribution about staying in the organization
8STATISTICS Table3: Frequency distribution of gender wise working hours Figure4: Frequency distribution of gender wise average working hours Table4: Frequency distribution of the variable “Influence”
9STATISTICS Figure5: Table of percentage frequencies of types of “Influence” Figure6: Table of frequencies of types of “Influence”
Paraphrase This Document
Need a fresh take? Get an instant paraphrase of this document with our AI Paraphraser
10STATISTICS Figure7: Scatter plot of “Weekly working hours” as dependent and “Age” as independent variable Figure8: Scatter plot of “Weekly working hours” as dependent and “Educational Years” as independent variable Figure9: Scatter plot of “Weekly working hours” as dependent and “Salary” as independent variable
11STATISTICS Figure10: Scatter plot of “Weekly working hours” as dependent and “Working Years” as independent variable Figure11: Scatter plot of “Weekly working hours” as dependent and “AtCuteen” as independent variable
12STATISTICS Figure12: Scatter plot of “Weekly working hours” as dependent and “NumPromo” as independent variable Table5: Correlation coefficient matrix
Secure Best Marks with AI Grader
Need help grading? Try our AI Grader for instant feedback on your assignments.