Hi, the assignment requires that I run Regression Assumptions and write the results / analyses of the assumptions in a paper. It is a continuation of question 9. Everything else is done. I just need...

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Hi, the assignment requires that I run Regression Assumptions and write the results / analyses of the assumptions in a paper. It is a continuation of question 9. Everything else is done. I just need to run regression assumptions and discuss them. Thanks.
Answered Same DayApr 25, 2021

Answer To: Hi, the assignment requires that I run Regression Assumptions and write the results / analyses of...

Mohd answered on Apr 26 2021
141 Votes
Linearity:
Each independent variables appears to be linearly related to dependent variable. As we can see from matrix scatter plot, all independent variables are linearly related to dependent variable satinst.
M
ulticollinearity
To check multicollinearity, we have drawn correlation matrix of independent variables. If there any pair of independent variable having correlation coefficient greater than 0.7, then multicollinearity is exist. As we can see from correlation matrix no independent variable pair has correlation greater than 0.7, which means there is no multicollinearity and assumption of multicollinearity has met. We can also check multicollinearity with variable inflation factor and tolerance.
Correlations
control
select
size
chgthink
chggen
chgfield
control
Pearson Correlation
1
.168**
-.492**
-.040
.038
-.037
Sig. (2-tailed)
.004
.000
.496
.520
.530
N
287
287
287
287
287
286
select
Pearson Correlation
.168**
1
.156**
.115
.049
.090
Sig. (2-tailed)
.004
.008
.052
.405
.129
N
287
287
287
287
287
286
size
Pearson Correlation
-.492**
.156**
1
.011
-.019
.000
Sig. (2-tailed)
.000
.008
.850
.746
.999
N
287
287
287
287
287
286
chgthink
Pearson Correlation
-.040
.115
.011
1
.379**
.300**
Sig. (2-tailed)
.496
.052
.850
.000
.000
N
287
287
287
287
287
286
chggen
Pearson Correlation
.038
.049
-.019
.379**
1
.309**
Sig. (2-tailed)
.520
.405
.746
.000
.000
N
287
287
287
287
287
286
chgfield
Pearson Correlation
-.037
.090
.000
.300**
.309**
1
Sig. (2-tailed)
.530
.129
.999
.000
.000
N
286
286
286
286
286
286
Residuals distribution:
Is the distribution generally normal?
Now we are checking normality of dependent variable residuals. As we can see from histogram it clearly indicates that, dependent variable residuals are normally distributed.
Homoscedasticity:
Are the dots generally following the dot line? Assumption of homoscedasticity has met.
Autocorrelation:
Are the dots scattered?
Not following a pattern?
Not clustered?
Standardized residuals vs regression...
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