a. Is there any reason to doubt the equal variance assumption made in the one-way ANOVA model in this particular case? Support your response to this question.
b. Assuming the variances of the four underlying populations are indeed equal, can you reject at the 10% significance level that the mean starting salary is the same for each of the given business majors? Explain.
Comparing the Impact of Four Different Majors on Starting Salaries
Accounting Marketing Finance Management
$31,450 $28,350 $29,325 $27,320
$35,650 $27,845 $29,550 $26,450
$32,630 $28,430 $31,640 $30,135
$37,110 $27,645 $32,760 $27,340
$29,440 $28,635 $30,550 $28,635
$37,330 * $29,875 *
$30,835 * $28,890 *
* * $31,650 *
Please see the attached file.
There does not seem to be any major difference in the variances of the four disciplines.
Hypotheses: H0: m1 = m2 = m3 = m4 vs. HA: At least one of the means is different
Level of Significance: a = 10%
Decision Rule: Reject the null hypothesis if p-value < 0.10
One factor ANOVA
Mean n Std. Dev
33,492.1 7 3,185.08 ...
This solution provides a null and alternative hypothesis on the differences of majors and their starting salaries. Test statistics are calculated and compared with a p-value to make a decision to accept or reject the null hypothesis on the relationship. All steps are shown in an Excel file.
Calculation of F test from ANOVA
Article about UK Supermarket Employees: The hypothesis is whether or not Age, Work Experience, or Gender has more of an effect on job satisfaction. We have to come up with a null hypothesis and alternate hypothesis and do an ANOVA test to determine.
The following are needed:
2 Degrees of Freedom Values
Critical F Value
Use .05 in type I error
ATTACHED PDF ARTICLE.View Full Posting Details