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Data Analysis and Maintenance Analytical Essay


The research under consideration is a hypothetical research scenario that involves a client supplier organization that is involved in the manufacture of steel products. The research project was carried out to address the problems of training ineffectiveness and employee satisfaction. The hypotheses of the research have been developed with the operationalization of the variables done. It is thus necessary to develop a data collection plan for the research which is presented in this paper.

Non-Survey Data

The factor of heat is an independent variable to be measured using the Predicted Mean Vote (PMV) scale which is a parameter for the assessment of thermal comfort. This variable depends is subjective since heat perception is based on the mind and individual interpretations (Weiss, 2002).

This thus has to make use of the heat thermal equations proposed by Fanger (1970). The four parameters for the environment shall be measured by a technical expert engineer in the fields of temperature, relative humidity, mean radiant temperature and air velocity. The personal parameters which are clothing and activity level shall be obtained from the Standard ISO 7730 and compared accordingly.

The other personal data such as the age, weight, height and personal characteristics of the employees shall be obtained from the survey. The thermal parameters are likely to experience environmental changes but this shall be overcome by measuring from 9.00AM in the morning to 5.00 PM in the evening in intervals of 1 minute (Weiss, 2002).

Survey Instrument

The survey instrument shall cover items that focus on obtaining information about the level of employee satisfaction, support of the instructor, training relevance, promotion and coworker support, payment, training opportunities (Johns, 2006). The survey instrument will contain the following items:

  1. Overall how satisfied are you based on the following statements (statements a to f below) (Please circle one number appropriately where 1 represents extremely dissatisfied, 2 represents very dissatisfied, 3 represents somewhat dissatisfied, 4 represents somewhat satisfied, 5 represents very satisfied and 6 represents extremely satisfied). Please answer the other questions by marking the most appropriate response for you.
    1. How do you feel about XYZ as your employer? 1 2 3 4 5 6
    2. How do you perceive the long term strategy of XYZ Company? 1 2 3 4 5 6
    3. Do you like the type of work you do? 1 2 3 4 5 6
    4. How do you feel about how your supervisor treats you? 1 2 3 4 5 6
    5. Do you feel that your salary is fair to the work you do? 1 2 3 4 5 6
    6. How satisfied are you with the amount of vacation? 1 2 3 4 5 6
  2. I received as much initial training as I needed Yes No
  3. There is an effective training program Yes/ No
  4. The training is an individual training and group based training Yes/ No
  5. The training process automatically leads to a salary increment True/ False
  6. The training I receive is relevant to my work True/ False
  7. The trainers are very supportive and understanding True/ False
  8. My coworkers support me in work True/ False

Statistical Tests for Data Analysis

The statistical tests for the correlation between employee satisfaction and payment levels shall be done using the structural equation model technique while the correlation between employee satisfaction and heat factor shall be done using regression analyses (Weiss, 2002).

The correlation between employee satisfaction and training opportunities and that between training effectiveness and training opportunities shall be tested using simple and multiple analyses. Hierarchical regression analyses shall be used to test the correlation between training effectiveness and performance appraisal as well as between training effectiveness and payment levels (Johns, 2006).

Research Approaches

There are no conflicting interpretations due to the quantitative nature of research, use of age cohorts and the individuality of the hypotheses. Moreover, the methods of analysis are related. This can however be avoided through increased objectivity (Johns, 2006).

Summary of Findings

The findings likely to be established are that there is a positive correlation between: employee satisfaction and payment levels; employee satisfaction and training opportunities; and training effectiveness and payment levels. On the other hand, the employee satisfaction is negatively correlated with heat factor.


This paper has provided the data collection plan for the hypothetical research problem. The plan includes the non-survey data, the survey instrument, data analysis, research approaches and summary of findings anticipated from the research.

Reference List

Fanger, P. (1970). Thermal Comfort. Copenhagen: Danish Technical Press.

Johns, G. (2006). The essential impact of context on organizational behavior. Academy of Management Review, 31, 396–408.

Weiss, H. M. (2002). Deconstructing job satisfaction: separating evaluations, beliefs and affective experiences. Human Resource Management Review, 12, 173-194.

This Analytical Essay on Data Analysis and Maintenance was written and submitted by user Madisyn Woods to help you with your own studies. You are free to use it for research and reference purposes in order to write your own paper; however, you must cite it accordingly.

Madisyn Woods studied at California State University, Sacramento, USA, with average GPA 3.54 out of 4.0.

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Woods, M. (2020, January 10). Data Analysis and Maintenance [Blog post]. Retrieved from

Work Cited

Woods, Madisyn. "Data Analysis and Maintenance." IvyPanda, 10 Jan. 2020,

1. Madisyn Woods. "Data Analysis and Maintenance." IvyPanda (blog), January 10, 2020.


Woods, Madisyn. "Data Analysis and Maintenance." IvyPanda (blog), January 10, 2020.


Woods, Madisyn. 2020. "Data Analysis and Maintenance." IvyPanda (blog), January 10, 2020.


Woods, M. (2020) 'Data Analysis and Maintenance'. IvyPanda, 10 January.

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