The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, Y=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant. Price in dollars 109 113 155 167 170 Number of Bids 10 11 12 13 17 Summation Table X Y XY X2 Y2 BID 1 109 10 1090 11881 100 BID 2 113 11 1243 12769 121 BID 3 155 12 1860 24025 144 BID 4 167 13 2171 27889 169 BID 5 170 17 2890 28900 289 SUM 714 63 9254 105464 823 Step 1: Find the estimated slope. Step 2: Find the estimated y-intercept. Step 3: Find the estimate value of y when x=113. Step 4: Determine if the statement "All points predicted by the linear model fall on the same line" is true or false. Step 5: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable y

Answered: The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider…

MATLAB: An Introduction with Applications

6th Edition

ISBN: 9781119256830

Author: Amos Gilat

Publisher: John Wiley & Sons Inc

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The table below gives the list price and the number of bids received for five randomly selected items sold through online auctions. Using this data, consider the equation of the regression line, Y=b0+b1x, for predicting the number of bids an item will receive based on the list price. Keep in mind, the correlation coefficient may or may not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.

Price in dollars	109	113	155	167	170
Number of Bids	10	11	12	13	17

Summation Table

	X	Y	XY	X2	Y2
BID 1	109	10	1090	11881	100
BID 2	113	11	1243	12769	121
BID 3	155	12	1860	24025	144
BID 4	167	13	2171	27889	169
BID 5	170	17	2890	28900	289
SUM	714	63	9254	105464	823

Step 1: Find the estimated slope.

Step 2: Find the estimated y-intercept.

Step 3: Find the estimate value of y when x=113.

Step 4: Determine if the statement "All points predicted by the linear model fall on the same line" is true or false.

Step 5: Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable y.

Step 6: Find the value of the coefficient of determination.

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