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, yˆ=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 statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.   Price in Dollars 21   26   28   35   43     Number of Bids 1   3   5   6   9 Step 3 of 6 :  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 yˆ. NOTE: Step 1 of 6:  Estimated slope =  Slope: 0.347 Step 2 of 6: Find y-intercept = y-intercept: -5.818           Regression Line: y= 0.347x + -5.818

MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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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, yˆ=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 statistically significant for the data given. Remember, in practice, it would not be appropriate to use the regression line to make a prediction if the correlation coefficient is not statistically significant.

 

Price in Dollars 21
  26
  28
  35
  43
   
Number of Bids 1
  3
  5
  6
  9
Step 3 of 6 : 

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 yˆ.

NOTE:

Step 1 of 6:  Estimated slope =  Slope: 0.347
Step 2 of 6: Find y-intercept = y-intercept: -5.818
         
Regression Line: y= 0.347x + -5.818  

.

 

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