1. Below is computer output from SPSS, the package used in the text. The table below has descriptive statistics for each variable measured the 5-point scale, with 5 being "Strongly Agree" and 1 being "Strongly Disagree" (Favorable = "SA or A")
a. Which variable is has the most favorable rating?
b. Which variable has the most variation in the response?
c. Below is a frequency distribution of the stress variable.
STRESS
Frequency Percent Cumulative Percent
Valid 1.00 37 18.3 18.3
2.00 20 9.9 28.2
3.00 45 22.3 50.5
4.00 45 22.3 72.8
5.00 55 27.2 100.0
Total 202 100.0
What percentage of respondents "Strongly Agree/Agree" with their stress level being reasonable?
What percentage of respondents "Strongly Disagree/ Disagree" with their stress level being reasonable?
2. In addition to the survey items, respondents were asked to report their age as follows:
My generation is (AGE) Generation Y (Born 1981-2000) 1
Generation X (Born 1965-1980) 2
Baby Boomers (1946-1964) 3
Veterans (Born 1922-1945) 4
Below is output from an ANOVA to test if there are differences in stress levels between age groups.
What was is the null hypothesis?
What is the alternative hypothesis?
Below are summary statistics for
STRESS
N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum
Lower Bound Upper Bound Lower Bound Upper Bound Lower Bound Upper Bound Lower Bound Upper Bound
1.00 83 4.1325 1.39486 .15311 3.8280 4.4371 1.00 11.00
2.00 45 3.0444 1.39733 .20830 2.6246 3.4642 1.00 5.00
3.00 37 2.4595 2.06283 .33913 1.7717 3.1472 1.00 11.00
4.00 37 3.1351 1.00449 .16514 2.8002 3.4701 1.00 5.00
Total 202 3.4010 1.60924 .11323 3.1777 3.6243 1.00 11.00
Which group has the lowest stress level? (1 pt)
Which group has the highest stress level? (1 pt)
Which group has the most variation in stress level? (1 pt)
Below is the ANOVA output.
ANOVA
STRESS
Sum of Squares df Mean Square F Sig. (P-value)
Between Groups 91.680 3 30.560 4.339 .041
Within Groups 322.899 198 1.631
Total 414.579 201
Are the results significant? Write a 2-3 sentence summary of your findings.
3. The organization that surveyed the employees wanted to know what factors influenced STRESS so they could take action. To do that a multiple regression analysis was run that regressed the all the items against the STRESS measure to see which ones had the most impact on stress. Below are the findings:
Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .742(a) .55 .53 1.39776
a Predictors: (Constant), REWARDS, LEARN, WORKLIFE, RESOURCES, INVOLVEMENT
ANOVA(b)
Model Sum of Squares df Mean Square F Sig.
1 Regression 30.233 5 6.047 3.095 .015(a)
Residual 357.533 183 1.954
Total 387.766 188
a Predictors: (Constant), REWARDS, LEARN, WORKLIFE, RESOURCES, INVOLVEMENT
b Dependent Variable: STRESS
Coefficients(a)
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta B Std. Error
1 (Constant) 1.992 .560 3.558 .000
RESOURCES .158 .123 .117 1.287 .200
WORKLIFE .148 .125 .104 2.131 .039
INVOLVEMENT .292 .136 .200 2.147 .033
LEARN .110 .112 .076 .978 .329
REWARDS .179 .134 .124 1.330 .185
a Dependent Variable: STRESS
What is the R-square and what does it mean?
Was the overall multiple regression significant?
Looking at each regression coefficient, which one(s), if any, are statistically significant?
Summarize the results in 2-3 sentences.