PREDICTION (REGRESSION) – Chapter 12
3. A researcher was interested in whether there was a relationship between stress and depression scores obtained from emergency health care providers. The data from 10 emergency workers are below. This is the same data you calculated a correlation on in Question 1. We are trying to use stress scores (IV or Predictor) to predict depression scores (DV or outcome). Using SPSS, calculate a linear regression model:
Y = a+b1X1 where Y is Depression and X1 is stress.
We actually could rewrite the equation as: Depression = a+b1Stress
Stress |
Depression |
38 |
26 |
28 |
16 |
42 |
34 |
18 |
22 |
26 |
15 |
45 |
24 |
32 |
18 |
26 |
18 |
22 |
12 |
33 |
15 |
Using the output:
Significance Level of b1 (i.e. “p-value”)? ___________
Significance Level of a (i.e. “p-value”)? ___________
Answer:
Given that,
A researcher was interested in whether there was a relationship between stress and depression scores obtained from emergency health care providers.
The data from 10 emergency workers are below. This is the same data you calculated a correlation on in Question 1.
We are trying to use stress scores (IV or Predictor) to predict depression scores (DV or outcome).
Calculate a linear regression model:
Y = a+b1X1 where Y is Depression and X1 is stress.
We actually could rewrite the equation as:
Depression = a+b1Stress
Stress | Depression |
38 | 26 |
28 | 16 |
42 | 34 |
18 | 22 |
26 | 15 |
45 | 24 |
32 | 18 |
26 | 18 |
22 | 12 |
33 | 15 |
Using SPSS, go to Data, select Data analysis, Choose regression. Put stress in X input range and depression in Y input range.
Summary Output | ||||||
Regression Statistics | ||||||
Multiple R | 0.647 | |||||
R-square | 0.418 | |||||
Adjusted R square | 0.345 | |||||
Standard error | 5.326 | |||||
Observations | 10 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 1 | 163.072 | 163.072 | 5.749 | 0.043 | |
Residual | 8 | 226.928 | 28.366 | |||
Total | 9 | 390.000 | ||||
Coefficients | Standard Error | t stat | P-value | Lower 95% | Upper 95% | |
Intercept | 4.819 | 6.552 | 0.736 | 0.483 | -10.289 | 19.927 |
Stress | 0.490 | 0.204 | 2.398 | 0.043 | 0019 | 0.961 |
(a).
b1=0.49
Standard error of b1=0.204
The p-value of b1=0.043
(b).
With one unit increase in stress, depression increases by 0.49 units.
(c).
Standardized value of b1 (Multiple R)=0.647
(d).
a=4.819
Standard error of a=6.552
The p-value of a=0.483
(e).
If there is no stress, the depression score will be 4.819.
(f).
y=4.819+0.49x
Stress=30
Depression=4.819+0.49(30)
=4.819+14.7
=19.519
PREDICTION (REGRESSION) – Chapter 12 3. A researcher was interested in whether there was a relationship...
3. A researcher was interested in whether there was a relationship between stress and depression scores obtained from emergency health care providers. The data from 10 emergency workers are below. This is the same data you calculated a correlation on in Question 1. We are trying to use stress scores (IV or Predictor) to predict depression scores (DV or outcome). Using SPSS, calculate a linear regression model: Ý a + b X where Y is Depression and X, is stress....
1. A researcher was interested in whether there was a relationship between stress and depression scores obtained from emergency health care providers. The data from 10 emergency workers are below. Stress Depression 38 26 28 16 42 34 18 22 26 15 45 24 32 18 26 18 22 12 33 15 Stress M = 31 , SD = 8.25 Depression M = 20, SD = 6.24 By hand, calculate the correlation coefficient. You are given the mean and standard...
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