Job satisfaction statistical analysis

Human resource theory suggests that job satisfaction is predicated upon correlation between job expectation and fulfillment of the stated expectation.  Subscribing to this theory, Murray and Cunningham (2004) assert that those “individuals whose expectations of the job are more closely aligned with the reality of the job are more likely to experience job satisfaction.”  To support the quoted hypothesis, Murray and Cunningham (2004) make extensive use of statistical data as shall be highlighted in this report.  However, and despite the fact that their usage of statistical data is accurate, Miner, Glomb and Hulin (2005) test the validity of a comparable hypothesis through the exploitation of a more precise methodology for statistical data collection.  Through an analysis of the usage of statistics in both the cited researches, this report shall conclude with the presentation of two sets of hypotheses which withstand testing validation through the use of ANOVAs.

Examining job satisfaction levels amongst a defined sample population of rural community college instructors, Murray and Cunningham (2004) presented one set of hypothesis.  The null hypothesis was that high turnover was due to job dissatisfaction, while the alternate hypothesis held that high turnover was due to a range of factors, with job satisfaction figuring as just one of them.  The authors proceeded to present statistical data collected from previous researches and which pertained to the gender, age and racial composition of the sample population, here defined as community college instructors.  The statistics presented at this stage did not contribute to the validation of either the null or the alternate hypothesis but more generally fortified the claim that job dissatisfaction was high among practitioners of this particular profession.  Therefore, at his point, one can critique the mentioned research on the basis of its having including statistics which may be deemed irrelevant with the context of the hypothesis set.

Following the presentation of statistical data on the composition of the sample population, Murray and Cunningham (2004) use statistics pertaining to self-reported intentions to take an early retirement or to resign the profession.  The criticism here is the same as above.  In brief, the statistics cited are relevant to neither the null nor the alternate hypothesis.  Certainly, the researchers proved the existence of a problem within the profession as indicated by statistics signaling that the greater majority planned to retire the profession.  However, while one may logically assume that the stated intention is reflective of job satisfaction, the fact is that this is an unproven assumption, unsupported by the set of statistics provided by the researchers.  Hence, within the context of this particular research, the statistical data employed proved high turnover ad a lack of organizational commitment but neither proven the null nor the alternate hypotheses.

Indirect comparison to the above discussed research, Miner, Glomb and Hulin (2005) employ statistical data which directly pertains to their null and alternate hypothesis on job satisfaction levels among a sample population of corporate employees.  The null hypothesis, that positive work experience is positively related to job satisfaction was supported through statistical data collected from quantitative questionnaires distributed among the sample population.  Insofar as referred to statistical data  focused on attitudes towards work hours, monetary compensation, the work environment and level of organizational commitment and demonstrated that those who reported high degrees of satisfaction in the mentioned areas reported high job satisfaction levels, statistics were accurately employed.  As pertains to the alternate hypothesis, that while job satisfaction is positively related to work satisfaction, the level of job satisfaction rises and fluctuates according to the time of the day and the day of the week the supporting statistical data was very precise.  Questionnaires distributed among the sample population asked the same questions as earlier cited but categorized them by morning, midday and late day and by time of the week.  Therefore, employees provided responses to the questions pertaining to job satisfaction three times during the work day and five times in the work week.  In their citation and discussion of the mentioned statistical data, the researchers were able to conclusively validate the alternate hypothesis.  Consequently as regards the use of statistics in this research on job satisfaction, as contrasted to the first, one may conclude that statistics were relevantly employed to test and validate the null and alternate hypothesis presented.

Based on the above cited research write-ups and elaboration on their usage of statistical data, one may forward the below sets of hypothesis, testable through the use of the one-way ANOVA.  The research question that will inform the sets of hypotheses is whether job satisfaction is higher for a group of tenured professors at rural community colleges than it is for part-time instructors at the same institutes?

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Hypothesis Set 1:

H₀:  Job satisfaction is equal for the two groups.

H₁: Job satisfaction is significantly lower for part-time instructors than it is for tenured professors.

Hypothesis Set 2:

H₀:  The factors influencing job satisfaction are the same for tenured professors at rural colleges as they are for part time instructors at the same colleges.

H₁: A different set of factors influences job satisfaction between the two groups.

Both sets of hypotheses, insofar as they are statistical hypotheses withstand validation through ANOVA tests.