The motivator-hygiene theory (Herzberg et al., 1959) suggested that salary is one of the hygiene factors, which are associated with employees’ negative feelings about the job. A local police chief wanted to improve the morale of his agency, and Professor X was invited to do a preliminary study for this project. First of all, Professor X wanted to know whether police officers of this agency had been paid differently. She surveyed 138 officers across six local police departments, and used SPSS to compare maximum salary of these six agencies. Following is the SPSS printout of One-way ANOVA F-test. Provide your appropriate interpretations and submit to the instructor in a timely manner (see Class Schedule).
|Sum of Squares||df||Mean Square||F||Sig.|
F = MSb / MSw = 2147153.922 / 191443.214
n = 138, k = 6
Theoretical Model: X (Maximum Salary) Y (employees’ negative feelings about the job)
Step 1: Formulation of the null and alternative hypotheses
H0: μ1 = μ2 = μ3, the means for all of these six groups are equal
HA: At least one of the group means is different from the others
Step 2: Determination of the level of significance
Upper-tailed test α < .005
Step 3: Determination of the critical value of the test statistic
By using Table A.5, α = 0.005
When d.f.w = n – k = 138 – 6 = 132
d.f.b = k – 1 = 6 – 1 = 5
F = MSb/MSw
= (10735770/5) / (25270504/132)
If F Ratio > 11.216 reject H0
Step 4: Computation of the test statistic
SPSS ANOVA table indicates F Ratio equals 11.2156 which is equal to 11.2156
The null hypothesis is not rejected. It means that we reject the alternative hypothesis.
Step 5: Make the conclusion in line with the test statistic
With respect to the data of 138 officers across six different local police departments, it is concluded that the maximum salary does not affect employees’ negative feelings about the job
Unit 9 Assignment: Read Table 2, find out each following Pearson correlation coefficient and significant level
- Assault-Monthly Salary
Pearson correlation is 0.317 at significant level of 0.01
- Assault-Jail Size
Pearson correlation is 0.175 at a significant level of 0.05
- Assault-Maximum Security Inmate
Pearson correlation is 0.174 at a significant level of 0.05
- Assault-Male Staff
Pearson correlation is 0.196 at a significant level of 0.05
- Jail Size-Month Salary
Pearson correlation is 0 263 at significant level of 0.01
Looking at the Pearson correlation coefficients above, it can be clearly deduced there is a positive correlation between assault and jail size, assault and maximum security inmate and assault and male staff and these are significant at a level of 0.05. On the other hand, at a significant level of 0.01, there is also a positive correlation between assault and monthly salary and jail size and monthly salary. However, it is a general observation from the figures that variables subjected to evaluation at 0.01 significant level exhibit a more positive relationship than those at 0.05. For instance, 0.263 > 0.175 (for jail size-monthly salary and assault-jail size).
Unit 10 Assignment: Interpret the following SPSS output. Type your interpretations and submit to the instructor in a timely manner
To aid in the interpretation of the SPSS printout, a restatement of the null hypothesis will help in giving direction in the interpretation. The tables indicate that the variables under scrutiny are type of misconduct and time misconduct happened.
The null hypothesis for the study would be: “there is no significant relationship between type of misconduct and time the misconduct happened.”
Looking at the results of the of SPSS chi-square test, we see that the two-tailed asymptotic significance is 0.04. Since this is less than 0.05 at a 95 % confidence level, we are justified to reject the null hypothesis and restate the null hypothesis that there is an actually significant relationship between the type of misconduct and time of misconduct (Hinton, 2001).
Hinton, P. R (2001) Statistics Explained, Revised Illustrated Edition; Routledge: 234- 267
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