Attached you will find the SPSS output for a regression analysis (See the following or attached file). The regression analysis was used to examine youths' depression levels (as measured by the CDI) and their exposure to community violence and child maltreatment (yes=1, no=0). Use the regression equation to answer the question. What is the Y' value for depression if a youth scored 7 on the community violence scale and was not maltreated (0)? Regression [CDI-Children’s Depression Inventory; CVTotal-Community Violence Exposure; Maltreatment (1-yes/0-no)] Descriptive Statistics Mean Std. Deviation N CDItotal 8.05 6.431 386 CVtotal 2.65 2.342 386 maltreatment .64 .481 386 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate Change Statistics R Square Change F Change df1 df2 Sig. F Change 1 .154(a) .024 .018 6.371 .024 4.621 2 383 .010 a Predictors: (Constant), abuse or comparison, CVtotal ANOVA(b) Model Sum of Squares df Mean Square F Sig. 1 Regression 375.167 2 187.583 4.621 .010(a) Residual 15545.994 383 40.590 Total 15921.161 385 a Predictors: (Constant), abuse or comparison, CVtotal b Dependent Variable: CDItotal Coefficients(a) Model Unstandardized Coefficients Standardized Coefficients t Sig. Correlations B Std. Error Beta Zero-order Partial Part 1 (Constant) 6.447 .630 10.231 .000 CVtotal .327 .139 .119 2.344 .020 .127 .119 .118 maltreatment 1.151 .678 .086 1.698 .090 .098 .086 .086 a Dependent Variable: CDItotal
Correlation
Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.
Linear Correlation
A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.
Regression Analysis
Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.
Attached you will find the SPSS output for a
Regression
[CDI-Children’s Depression Inventory; CVTotal-Community Violence Exposure; Maltreatment (1-yes/0-no)]
|
|
Mean |
Std. Deviation |
N |
|
CDItotal |
8.05 |
6.431 |
386 |
|
CVtotal |
2.65 |
2.342 |
386 |
|
maltreatment |
.64 |
.481 |
386 |
Model Summary
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
Change Statistics |
||||
| R Square Change |
F Change |
df1 |
df2 |
Sig. F Change |
|||||
|
1 |
.154(a) |
.024 |
.018 |
6.371 |
.024 |
4.621 |
2 |
383 |
.010 |
a Predictors: (Constant), abuse or comparison, CVtotal
ANOVA(b)
|
Model |
|
Sum of Squares |
df |
Mean Square |
F |
Sig. |
|
1 |
Regression |
375.167 |
2 |
187.583 |
4.621 |
.010(a) |
| Residual |
15545.994 |
383 |
40.590 |
|
|
|
| Total |
15921.161 |
385 |
|
|
|
a Predictors: (Constant), abuse or comparison, CVtotal
b Dependent Variable: CDItotal
Coefficients(a)
|
Model |
|
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
|
|||
| B |
Std. Error |
Beta |
Zero-order |
Partial |
Part |
||||
|
1 |
(Constant) |
6.447 |
.630 |
|
10.231 |
.000 |
|
|
|
| CVtotal |
.327 |
.139 |
.119 |
2.344 |
.020 |
.127 |
.119 |
.118 |
|
| maltreatment |
1.151 |
.678 |
.086 |
1.698 |
.090 |
.098 |
.086 |
.086 |
a Dependent Variable: CDItotal
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