Indicate the following conclusions that can be made based on your analysis of th
ID: 3243684 • Letter: I
Question
Indicate the following conclusions that can be made based on your analysis of the predictors of stress and their significance. Note that significant is when p<.05. Select more than one option below.
Remember, if a variable is not significant, then we do not make any conclusions or interpretations of how that variable influences stress (because it does NOT influence alcohol use).
a. NONE of these variables are significant predictors of stress.
b. For every one hour increase in sleep, we can expect a .33 point increase in stress on the stress scale.
c. For every one hour increase in sleep, we can expect a .33 point decrease in stress on the stress scale.
d. For every one point increase in stress, we can expect a .308 point increase in sleep.
e. For every one point increase in stress, we can expect a .308 point decrease in sleep.
f. Sleep and stress are not significantly related.
g. Men are significantly more stressed than women.
h. Women are significantly more stressed than men.
I. Men and women do not significantly differ in stress.
j. For every one year increase in age, we can expect a .005 point increase in stress on the stress scale.
k. For every one year increase in age, we can expect a .005 point decrease in stress on the stress scale.
L. For every one year increase in age, we can expect a .028 point increase in stress on the stress scale.
M. For every one year increase in age, we can expect a .028 point decrease in stress on the stress scale.
a. NONE of these variables are significant predictors of stress.
b. For every one hour increase in sleep, we can expect a .33 point increase in stress on the stress scale.
c. For every one hour increase in sleep, we can expect a .33 point decrease in stress on the stress scale.
d. For every one point increase in stress, we can expect a .308 point increase in sleep.
e. For every one point increase in stress, we can expect a .308 point decrease in sleep.
f. Sleep and stress are not significantly related.
g. Men are significantly more stressed than women.
h. Women are significantly more stressed than men.
I. Men and women do not significantly differ in stress.
j. For every one year increase in age, we can expect a .005 point increase in stress on the stress scale.
k. For every one year increase in age, we can expect a .005 point decrease in stress on the stress scale.
L. For every one year increase in age, we can expect a .028 point increase in stress on the stress scale.
M. For every one year increase in age, we can expect a .028 point decrease in stress on the stress scale.
Variables Entered/Removeda Variables Variables Model Entered Removed Method sleep, age, Enter gender a. Dependent Variable: stress b. All requested variables entered Model Summary Adjusted R Std. Error of Mode R the Estimate Square R Square .327a 1.396 .085 .107 a. Predictors: (Constant), sleep, age, gender a ANOVA Sum of df Mean Square F Sig. Squares Model 3 9.266 4.755 27.799 004 Regression Residual 119 1.949 231.909 Total 259.707 122 a. Dependent Variable: stress b. Predictors: (Constan), sleep, age, genderExplanation / Answer
Here the problem is of multiple regression.
Dependent variable is stress and there are three independent variables namely age, gender and sleep.
The regression equation is,
Stress = 6.839 - 0.005*age + 0.685*gender - 0.333*sleep
Here intercept = 6.839
Coefficient of age = -0.005
Coefficient of gender = 0.685
Coefficient of sleep = - 0.333
Coefficient of age, gender and sleep are known as slope coeffcients.
Interpretation of Slopes : If we fixed gender and sleep then one unit change in age will be 0.005 unit decrease in stress.
If we fixed age and sleep then one unit change in gender will be 0.685 unit increase in stress.
If we fixed age and gender then one unit change in sleep will be 0.333 unit decrease in stress.
-----------------------------------------------------------------------------------------------------------------
Test of significance we can do using t-test.
Here we have to test the hypothesis that,
H0 : B = 0 Vs H1 : B not= 0
where B is population slope for independent variable.
Assume alpha = level of significance = 0.05
Here test statistic follows t-distribution.
Decision rule :
If P-value < Alpha then reject H0 at 0.05 level of significance otherwise accept H0.
Conclusion : The variable is significant.
We see that P-value for age and gender are 0.763 and 0.072 respectively which are greator than alpha.
Accept H0 at 0.05 level of significance.
Conclusion : The population age and gender is differ than 0.
Also age and gender are insignificant variables.
And P-value for sleep is 0.001 which is less than alpha.
Reject H0 at 0.05 level of significance.
COnclusion : The population sleep for sleep may be 0.
Sleep is significant variablec.
For every one hour increase in sleep, we can expect a .33 point decrease in stress on the stress scale..
For every one year increase in age, we can expect a .005 point decrease in stress on the stress scale.
Related Questions
drjack9650@gmail.com
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.