Statistical Analysis

Research Summary

This research was implemented to a whether a relationship exists, connecting job satisfaction by theoretical use of work-related and organizational commitments, and how it relates towards age, gender, knowledge or skill, marital status, and designated variances. Organizational commitment essentially evaluates an employee’s commitment to their place of work where a company’s success is what drives the individual. Throughout the years, this term has been broken up into 3 multi-dimensional themes: affective, continuance, and normative commitment. These significant multi-dimensional areas of commitment are crucial for the reason that the more that is known about these areas, the more accurate an evaluation of the individual’s work relationships can be.

In the study, Professor Cetin analyzed data from an N-value of 132 academics across 4 universities in Turkey. To acquire his data, Professor Cetin sent out a personal data form, along with a 3 scale test consisting of a job satisfaction questionnaire, occupational commitment scale, and an organizational commitment scale. He utilized the t-test, one-way ANOVA, and the Pearson Moments Multiple Correlation Techniques to analyze his collected data from the previously stated methods. In our group project, we will concentrate on the ANOVA test; it is a much simpler technique to use when the means of three or more populations are being analyzed. For example, the t-test can only analyze two means at any given time, whereas the F-test can analyze more than three simultaneously with a more precise result. The more means which are in a population can lead to a miscalculation in the t-test, resulting in a rejection of a null hypothesis; this is unacceptable for our evaluation.

Introduction

For this report we will utilize the F-test to find whether a difference concerning age is relevant to job satisfaction. There are five steps in an F-test, which will be explained, in detail, further in this report. First, the hypothesis is required to be stated and the claim will have to be identified. Second, critical values must be attained. Next, steps three and four consist of testing the data and choosing whether to reject or accept the null hypothesis. Finally, in step five we will summarize our results.

F-test

Step 1: Declare a hypothesis and decide on a claim.

Null hypothesis: In regards to the Overall Satisfaction, which pertains to each age level, it seems that the significant difference, if any, will be negligible. As for the alternate hypothesis: In regards to the Overall Satisfaction, which pertains to each age level, it seems that it will have a significant difference. Presuming the Null Hypothesis conclusion is accurate, the data will remain unless it is proven inaccurate. However, as a group, we will attempt to acquire support by applying an alternate hypothesis

(claim)

At least one mean is different from the others.

Step 2: Find the critical value.

In order to acquire the critical value:

Calculate: Degrees of freedom. As for the F-test, these d.f. are equal to 2, one is called d.f.N., which means degrees of freedom numerator, and the other is d.f.D., which means degrees of freedom denominator. We need two values for these formulas to be calculated, N and k. N is the number of people surveyed, k regards the amount of groups in the survey. We see that there are 132 people in this survey and we will use the age variable, in which there are 3 groups.

The formula for d.f.N. is . To find d.f.D. we use another formula: . Professor Cetin stated in his report that he used a significance level or alpha level of 0.05. We now have the 3 values required to find a critical value. On page 640 of our text resides the table we will use to find our critical value. With an alpha level of 0.05, a d.f.N. of 2 and a d.f.D. of 129 we find our critical value is 3.00.

Step 3: Compute test value

a) Find mean and variance of each sample.

Our article did not provide a data set, means or variances; we fabricated these to run the F-test and provide an example of how step 3 can be performed.

20-30 31-40 40&over

n 44 44 44

3.6 3.54 3.58

1.43 2.68 2.44

b) Find the grand mean.

In order for this to be done, the data set we created