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A Regression Analysis Between Sales (In $1000) and Advertising (In

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A regression analysis between sales (in $1000) and advertising (in $) yielded the least squares line  A regression analysis between sales (in $1000) and advertising (in $) yielded the least squares line   = 80 000 + 5x. This implies that an:  \begin{array}{|l|l|} \hline A&\text {increase of  \$ 1  in advertising is expected to result in an increase of  <span class=$5 \$ 5 in sales. }\\ \hline B&\text { increase $5 \$ 5 in advertising is expected to result in an increase of $5000 \$ 5000 in sales.}\\ \hline C&\text { increase of $1 \$ 1 in advertising is expected to result in an increase of $80005 \$ 80005 in sales. }\\ \hline D&\text {increase of $1 \$ 1 in advertising is expected to result in an increase of $5000 \$ 5000 in sales. }\\ \hline \end{array} " class="answers-bank-image d-inline" rel="preload" > = 80 000 + 5x. This implies that an: Aincrease of $1 in advertising is expected to result in an increase of $5 in sales. B increase $5 in advertising is expected to result in an increase of $5000 in sales.C increase of $1 in advertising is expected to result in an increase of $80005 in sales. Dincrease of $1 in advertising is expected to result in an increase of $5000 in sales. \begin{array}{|l|l|}\hline A&\text {increase of \( \$ 1 \) in advertising is expected to result in an increase of \( \$ 5 \) in sales. }\\\hline B&\text { increase \( \$ 5 \) in advertising is expected to result in an increase of \( \$ 5000 \) in sales.}\\\hline C&\text { increase of \( \$ 1 \) in advertising is expected to result in an increase of \( \$ 80005 \) in sales. }\\\hline D&\text {increase of \( \$ 1 \) in advertising is expected to result in an increase of \( \$ 5000 \) in sales. }\\\hline \end{array}

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