In this study, the researcher is interested in predicting Feelings of Social Iso
ID: 3262885 • Letter: I
Question
In this study, the researcher is interested in predicting Feelings of Social Isolation (outcome variable) using Age, Drug Use, and Father’s Negligence as predictor variables. Using the Regression/Linear function, conduct the simple regression analysis for each of the predictor variables of Age, Drug Use, and Father’s Negligence, with Feelings of Social Isolation as the outcome variable.
QUESTION: a. Briefly compare the simple regression results.
b. Briefly discuss the gain in understanding from moving from three single regressions to one regression with three predicting variables.
c. Present two tables in APA style. In Table 1, show the multiple regression results for the Forced entry regression model, including the Collinearity statistics. In Table 2, show the regression ANOVA.
d. Discuss each of these two tables, including a discussion of the Durbin-Watson test and of the Collinearity statistic.
Data is listed below:
Descriptives
Statistic
Std. Error
Age
Mean
16.1234
.08715
95% Confidence Interval for Mean
Lower Bound
15.9508
Upper Bound
16.2959
5% Trimmed Mean
16.1202
Median
16.1700
Variance
.919
Std. Deviation
.95862
Minimum
14.50
Maximum
18.50
Range
4.00
Interquartile Range
1.71
Skewness
-.019
.220
Kurtosis
-1.030
.437
Drug Use
Mean
7.0346
.29261
95% Confidence Interval for Mean
Lower Bound
6.4552
Upper Bound
7.6140
5% Trimmed Mean
6.8906
Median
6.0000
Variance
10.360
Std. Deviation
3.21876
Minimum
3.00
Maximum
15.00
Range
12.00
Interquartile Range
4.50
Skewness
.601
.220
Kurtosis
-.708
.437
Father Negligence
Mean
17.7934
.60688
95% Confidence Interval for Mean
Lower Bound
16.5918
Upper Bound
18.9950
5% Trimmed Mean
17.4564
Median
16.0000
Variance
44.565
Std. Deviation
6.67572
Minimum
9.00
Maximum
35.00
Range
26.00
Interquartile Range
10.00
Skewness
.690
.220
Kurtosis
-.513
.437
Tests of Normality
Kolmogorov-Smirnova
Shapiro-Wilk
Statistic
df
Sig.
Statistic
df
Sig.
Age
.084
121
.034
.961
121
.001
Drug Use
.158
121
.000
.913
121
.000
Father Negligence
.134
121
.000
.926
121
.000
a. Lilliefors Significance Correction
Regression
Descriptive Statistics
Mean
Std. Deviation
N
Drug Use
7.0346
3.21876
121
Father Negligence
17.7934
6.67572
121
Correlations
Drug Use
Father Negligence
Pearson Correlation
Drug Use
1.000
.229
Father Negligence
.229
1.000
Sig. (1-tailed)
Drug Use
.
.006
Father Negligence
.006
.
N
Drug Use
121
121
Father Negligence
121
121
Variables Entered/Removeda
Model
Variables Entered
Variables Removed
Method
1
Father Negligenceb
.
Enter
a. Dependent Variable: Drug Use
b. All requested variables entered.
Model Summaryb
Model
R
R Square
Adjusted R Square
Std. Error of the Estimate
Change Statistics
Durbin-Watson
R Square Change
F Change
df1
df2
Sig. F Change
1
.229a
.053
.045
3.14624
.053
6.596
1
119
.011
1.857
a. Predictors: (Constant), Father Negligence
b. Dependent Variable: Drug Use
ANOVAa
Model
Sum of Squares
df
Mean Square
F
Sig.
1
Regression
65.294
1
65.294
6.596
.011b
Residual
1177.957
119
9.899
Total
1243.251
120
a. Dependent Variable: Drug Use
b. Predictors: (Constant), Father Negligence
Coefficientsa
Model
Unstandardized Coefficients
Standardized Coefficients
t
Sig.
Correlations
Collinearity Statistics
B
Std. Error
Beta
Zero-order
Partial
Part
Tolerance
VIF
1
(Constant)
5.069
.817
6.202
.000
Father Negligence
.110
.043
.229
2.568
.011
.229
.229
.229
1.000
1.000
a. Dependent Variable: Drug Use
Collinearity Diagnosticsa
Model
Dimension
Eigenvalue
Condition Index
Variance Proportions
(Constant)
Father Negligence
1
1
1.937
1.000
.03
.03
2
.063
5.534
.97
.97
a. Dependent Variable: Drug Use
Residuals Statisticsa
Minimum
Maximum
Mean
Std. Deviation
N
Predicted Value
6.0630
8.9359
7.0346
.73764
121
Std. Predicted Value
-1.317
2.577
.000
1.000
121
Standard Error of Predicted Value
.286
.794
.391
.104
121
Adjusted Predicted Value
5.9482
8.8636
7.0318
.73617
121
Residual
-4.94140
6.50059
.00000
3.13310
121
Std. Residual
-1.571
2.066
.000
.996
121
Stud. Residual
-1.587
2.078
.000
1.004
121
Deleted Residual
-5.04666
6.57767
.00282
3.18544
121
Stud. Deleted Residual
-1.598
2.108
.003
1.010
121
Mahal. Distance
.001
6.643
.992
1.203
121
Cook's Distance
.000
.124
.008
.014
121
Centered Leverage Value
.000
.055
.008
.010
121
a. Dependent Variable: Drug Use
Descriptives
Statistic
Std. Error
Age
Mean
16.1234
.08715
95% Confidence Interval for Mean
Lower Bound
15.9508
Upper Bound
16.2959
5% Trimmed Mean
16.1202
Median
16.1700
Variance
.919
Std. Deviation
.95862
Minimum
14.50
Maximum
18.50
Range
4.00
Interquartile Range
1.71
Skewness
-.019
.220
Kurtosis
-1.030
.437
Drug Use
Mean
7.0346
.29261
95% Confidence Interval for Mean
Lower Bound
6.4552
Upper Bound
7.6140
5% Trimmed Mean
6.8906
Median
6.0000
Variance
10.360
Std. Deviation
3.21876
Minimum
3.00
Maximum
15.00
Range
12.00
Interquartile Range
4.50
Skewness
.601
.220
Kurtosis
-.708
.437
Father Negligence
Mean
17.7934
.60688
95% Confidence Interval for Mean
Lower Bound
16.5918
Upper Bound
18.9950
5% Trimmed Mean
17.4564
Median
16.0000
Variance
44.565
Std. Deviation
6.67572
Minimum
9.00
Maximum
35.00
Range
26.00
Interquartile Range
10.00
Skewness
.690
.220
Kurtosis
-.513
.437
Explanation / Answer
Here dependent variable is drug use and independent variable is father negligence.
We have given some outputs.
We have given regression results.
Tests of normality :
Here we can test the hypothesis that,
H0 : The data follows normal distribution.
H1 : Data does not follows normal distribution.
Assume alpha = level of significance = 0.05
There are two methods given one is Kolmogorov Smirnov and Shapiro wilk test.
We see that P-value is age, drug use and father negligence are 0.034, 0.000, and 0.000 respectively.
P-value are < alpha
Reject H0 at 0.05 level of significance.
Therefore data does not follows normal distribution.
COrrelation between drug use and father negligance is 0.229.
We see that there is positive relationship between drug use and father negligance.
R-sq = 0.053
It expressee the proportion of variation in drug use which is explained by variation in father negligance.
Also we can test overall significance and individual signiifcance.
Here we can test the hypothesis that,
H0 : Bj = 0 Vs H1 : Bj not= 0
Or H0 : B = 0 Vs H1 : B not= 0
Foroverall significance test statistic follows F-distribution and for individual significance test statistic follows t-distribution.
The p-value for overall significance and individual significance is 0.011.
P-value < alpha
Reject H0 at 5% level of significance.
Conclusion : The population slope for father negligance is differ than 0.
We get significant result.
VIF = 1.000
It interpret as there is less multicollinearity problem.
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