The correlations table below indicates that: Correlations
$\begin{array}{|l|l|r|r|}
\hline & & {\text { Sales }} & \begin{array}{r}
\text { Advertising } \
\text { expenditure }
\end{array} \
\hline \text { Sales } & \text { Pearson correlation } & 1 & 0.753 (^{* *}) \
\hline & \text { Sig. (two-tailed) } & & 0.005 \
\hline & N & 100 & 100 \
\hline \begin{array}{l}
\text { Adverting } \
\text { expenditure }
\end{array} & \text { Pearson correlation } & 0.753 (^{* *})& 1 \
\hline & \text { Sig. (two-tailed) } & 0.000 & \
\hline & N & 100 & 100 \
\hline
\end{array}$ ** Correlation is significant at the 0.01 level (two-tailed).
A) about 75 per cent of variance in sales can be explained by the variance in advertising expenditure.
B) about 57 per cent of the variance in advertising expenditure can be explained by the variance in sales.
C) about 57 per cent of the variance in sales can be explained by the variance in advertising expenditure.
D) about 75 per cent of the variance in advertising expenditure can be explained by the variance in sales.

Question

Quizplus · Accepted Answer

The Pearson correlation coefficient between Sales and Advertising expenditure is 0.753, which is a strong positive correlation. This indicates that there is a significant relationship between Sales and Advertising expenditure. The correlation coefficient also indicates that about 57% of the variance in sales can be explained by the variance in advertising expenditure. Therefore, option C is the correct answer. Options A and D are incorrect because they state that 75% of the variance in either sales or advertising expenditure can be explained by the variance in the other variable, which is not supported by the given correlation table. Option B is incorrect because it states that 57% of the variance in advertising expenditure can be explained by the variance in sales, which is the opposite of the actual correlation presented in the table.

The Correlations Table Below Indicates That: Correlations ** Correlation Is Significant at the 0