A regression analysis between sales (Y in $100) and advertising (X in dollars) resulted in the following equation = 30,000 + 6 X The above equation implies that an
a. increase of $1 in advertising is associated with an increase of $600 in sales
b. increase of $1 in advertising is associated with an increase of $6 in sales
c. increase of $1 in advertising is associated with an increase of $6,000 in sales
d. None of the above
ycap = 30000 + 6x
for every 1 dollar increase in x, the y will increase by 600
increase of $1 in advertising is associated with an increase of $600 in sales
option A
A regression analysis between sales (Y in $100) and advertising (X in dollars) resulted in the...
Question 14 A regression analysis between sales (Yin $1,000) and advertising (X in dollars) resulted in the following equation Y = 30,000+ 4X. The equation implies that an: Increase of $4 in advertising is associated with an increase of $4.000 in sales Increase of $1 in advertising is associated with an increase of $4,000 in sales Increase of $1 in advertising is associated with an increase of $34.000 in sales - Previous Next → No new data to save. Last...
b Multiple Choice 14-019 A regression analysis between sales u in $tooo) and advertising (x in dollars) resulted in the following equation: Y = 30,000 + 4x The above equation implies that an O a. increase of $1 in advertising is associated with an increase of $4 in sales. O b. increase of $1 in advertising is associated with an increase of $4000 in sales. O c. increase of $4 in advertising is associated with an increase of $4000 in...
A regression analysis between sales (in $1000) and price (in dollars) resulted in the following equation y = 50,000-8x The above equation implies that an a increase of $1 in price is associated with a decrease of $42,000 in sales b increase of $1 in price is associated with a decrease of $8000 in sales c increase of Ss in price is associated with an increase of $8000 in sales d increase of $1 in price is associated with a decrease of $8 in sales
Regression analysis was applied between sales (Y in $1000) and advertising (X in $10,000), and the following estimated regression equation was obtained Based on the above estimated regression line if advertising is $10,000, then the point estimated for sales (in dollars) is a.503 b. 5030 c. 50,300 d.503,000 Ÿ=500+ 3x
#1 In simple linear regression, r is the: a) coefficient of determination. b) mean square error. c) correlation coefficient. d) squared residual. #2 In regression analysis, with the model in the form y = β0 + β1x + ε, x is the a) estimated regression equation. b) y-intercept. c) slope. d) independent variable. #3 A regression analysis between sales (y in $1,000s) and advertising (x in dollars) resulted in the following equation. ŷ = 40,000 + 3x The above equation...
Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained. ^y = 80 + 6.2x Based on the above-estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is $62,080 $142,000 $700 $700,000
2. Regression analysis was applied between sales (in $1,000) and advertising (in $100), and the following regression function was obtained Y=80+6.2x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is According to my quiz the answer is 700,000 , please help me figure out how.
A regression between the sales (Y) and the monthly advertising expenditures (X) resulted in the following predicted regression equations: = 10.9 + 0.23 x One observation in the sample data set shows that one store spend $68 K in advertising with sales of $29 K . What is the predicted sales for this store? $ 33 K $26.54 K $17.57 K $29.03 K
1. If an estimated regression line has a y-intercept of 10 and a slope of 4, then when x = 2 the actual value ofy is: а. 18 b. 15 с. 14 d. unknown 2. Given the least squares regression line v = 5- 2x: a. the relationship between x and y is positive b. the relationship between x and y is negative. c. asx decreases, so does y. d. None of these choices. 3. A regression analysis between weight...
21. A regression analysis between demand (y in 1000 units) and price (x in dollars) resulted in the following equation y-hat 9- 3x The above equation implies that if the price is increased by $1, the demand is expected to increase by 6 units decrease by 3 units decrease by 6,000 units decrease by 3,000 units a. c. d. 22. (12) An experimenter wishes to test if there is a significant difference in the average quality rating of wines from...