This research report discusses about the impact of age, department, tenure, gender and position on the samples drawn. The gender disparity and its impact on the job satisfaction, how male and female get satisfied with their job. This particular issue was deemed relevant due to its depth and impact on virtually all aspects of an organization.
A survey was conducted to determine the influence of gender, position, age, department and tenure on job satisfaction. The survey consisted of similar questions on job satisfaction with response options. The participant answered by selecting a value on a seven-point scale.
The answers are marked and merged, through a excel, into a personality profile which represents how strongly each of the basic desires features. This was handled anonymously. The results are presented in an easy to use graphics along with a comprehensive assessment report.
The scales were formed by adding the values of the individual questions of the scales by giving equal weight to each question. All categorical items on workload and strain were transformed on a value range from 1 (least satisfied) to 7 (most satisfied). In this case, the questions had seven response options with value of 1, 2, 3, 4, 5, 6 and 7.
The scale value is computed as the simple average. Answer refusals or participants that answered less than half of the questions are considered missing. For the participants that answered at least half, the scale value was computed as the average of the answered questions.
The variables chosen were gender for qualitative variable and Extrinsic for your quantitative variable.
Difference in variable types
A qualitative variable sometimes-called predictor variable. It is varied and manipulated by a researcher. It is referred to as presumed cause of an event.
It determines the value of other variables. It is manipulated to create an effect on other variable (Bhattacharya and Johnson, 1997).). Quantitative variables are the variables, which a researcher/experimenter measures after altering other variables which affect quantitative variable (Wierenga & Bruggen, 1998).
This case is sufficient to understand the significance of both the quantitative and qualitative variables in a quantitative research methodology. The values of qualitative variables are derived from quantitative variables which can be altered further by variation the values of quantitative variables(Healy, 2009).
Qualitative variable is considered as presumed cause of an event where as a quantitative variable is considered as the presumed effect of an event. The major difference between an qualitative and a quantitative variable is that quantitative values of qualitative variable can be altered by changing the values of the qualitative variable. It means that the values of qualitative variable are constant while those of quantitative variables are prior to changes (Babbie, 2009).
Descriptive statistics: Qualitative variable