A regression analysis between y, sales (in $1000) and x, advertising (in $) yielded the least squares line  = 60 + 5x. We can interpret the slope by saying that we estimate for each extra $1 spent on advertising that sales will increase by $5 000, on average.Group of answer choicesTrueFalse

A regression analysis between sales (in $1000) and advertising (in $100) yielded the least squares line = 75 +6x. This implies that if $800 is spent on advertising, then the predicted amount of sales (in dollars) is:Group of answer choices$487 500.$12 300.$123 000.$4875.

Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained.y-hat = 87 + 7.8 xBased on the above estimated regression line, if advertising is $11,924, then the point estimate for sales (in dollars) is

Suppose the linear regression line y = 2.1x + 130 predicts sales based on the money spent on advertising. If x represents the dollars spent in advertising, and y represents the company sales in dollars, about how much can the company expect in sales if it spends $50 in advertising?A.$650B.$105C.$323D.$235

In order to analyze sales as a function of advertising expenses, the sales manager developed a simple regression model. The model included the following equation, which was based on 32 monthly observations of sales and advertising expenses with a related coefficient of determination of .90.Sales = $10,000 + (2.5 × Advertising expenses)If the advertising expenses in 1 month amounted to $1,000, the related point estimate of sales would be

A simple linear regression model was run to understand the relationship between:price in thousands of dollars (P)sales in dollars (S)The model output the following equation:S = 50,000 – 8P Which of the following is true about the relationship between sales and price?An increase of $1 in price is associated with a decrease of $8,000 in salesAn increase of $1 in price is associated with a decrease of $80 in salesAn increase of $1 in price is associated with a decrease of $42,000 in salesAn increase of $8 in price is associated with an increase of $8,000 in sales