Refer to the following correlation matrix that was part of a regression analysis. The dependent variable was Abort (the number of abortions per 1000 women of childbearing age). The regression was estimated using data for the 50 U.S. states with these predictors: EdSpend = public K-12 school expenditure per capita, Age = median age of population, Unmar = percent of total births by unmarried women, Infmor = infant mortality rate in deaths per 1000 live births. $$\begin{array}{l}
\text { Correlation Matrix }\
\begin{array} { l c c c c c }
\hline & \text { Abort } & \text { EdSpend } & \text { Age } & \text { Unmar } & \text { InfMor } \
\hline \text { Abort } & 1.0000 & & & & \
\text { EdSpend } & 0.2626 & 1.0000 & & & \
\text { Age } & 0.1610 & - 0.0420 & 1.0000 & & \
\text { Unmar } & 0.3286 & - 0.0949 & 0.0937 & 1.0000 & \
\text { InfMor } & - 0.2513 & - 0.2826 & 0.0389 & 0.5239 & 1.0000 \
\hline
\end{array}
\end{array}$$ Using a two-tailed correlation test, which statement is not accurate?
A)Age and Infmor are not significantly correlated at ? = .05.
B)Abort and Unmar are significantly correlated at ? = .05.
C)Unmar and Infmor are significantly correlated at ? = .05.
D)The first column of the table shows evidence of multicollinearity.

Question

Refer to the following correlation matrix that was part of a regression analysis. The dependent variable was Abort (the number of abortions per 1000 women of childbearing age). The regression was estimated using data for the 50 U.S. states with these predictors: EdSpend = public K-12 school expenditure per capita, Age = median age of population, Unmar = percent of total births by unmarried women, Infmor = infant mortality rate in deaths per 1000 live births. $$\begin{array}{l}
\text { Correlation Matrix }\
\begin{array} { l c c c c c } 
\hline & \text { Abort } & \text { EdSpend } & \text { Age } & \text { Unmar } & \text { InfMor } \
\hline \text { Abort } & 1.0000 & & & & \
\text { EdSpend } & 0.2626 & 1.0000 & & & \
\text { Age } & 0.1610 & - 0.0420 & 1.0000 & & \
\text { Unmar } & 0.3286 & - 0.0949 & 0.0937 & 1.0000 & \
\text { InfMor } & - 0.2513 & - 0.2826 & 0.0389 & 0.5239 & 1.0000 \
\hline
\end{array}
\end{array}$$ Using a two-tailed correlation test, which statement is not accurate?
A)Age and Infmor are not significantly correlated at ? = .05.
B)Abort and Unmar are significantly correlated at ? = .05.
C)Unmar and Infmor are significantly correlated at ? = .05.
D)The first column of the table shows evidence of multicollinearity.

Quizplus · Accepted Answer

The correlation coefficient between Abort and EdSpend is positive but not very strong (r = 0.2626) which suggests that there is a weak relationship between these two variables. The correlation coefficient between Abort and Unmar is positive and moderately strong (r = 0.3286), indicating that there is a significant correlation between these two variables at α = .05. The correlation coefficient between Unmar and Infmor is also positive and moderately strong (r = 0.5239), indicating that there is a significant correlation between these two variables at α = .05. However, the correlation coefficient between Age and Infmor is small (r = 0.0389) and not significant at α = .05, suggesting that these two variables are not significantly correlated. Based on the correlation coefficients in the first column of the table, there is no evidence of multicollinearity, as the highest correlation coefficient is only moderate (r = 0.3286). Therefore, the inaccurate statement is D, which suggests that there is evidence of multicollinearity in the data.

Refer to the Following Correlation Matrix That Was Part of a Regression