Question

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, ý = bo + 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 Number of Bids 130 13 156 14 168 16 178 18 184 19 Table Copy Data Step 1 of 6: Find the estimated slope. Round your answer to three decimal places. Answer (How to Enter) 2 Points = Keypad

Answer 1

The statistical software output for this problem is:

Simple linear regression results: Dependent Variable: Bids Independent Variable: Dollars Bids = -2.3832021 + 0.11264217 Dollars Sample size: 5 R (correlation coefficient) = 0.94470767 R-sq = 0.89247258 Estimate of error standard deviation: 0.96535193 Parameter estimates: Parameter Estimate Std. Err. Alternative DF T-Stat Intercept -2.3832021 3.7092358 0 3 -0.64250488 Slope 0.11264217 0.02257369 0 3 4.9899759 P-value 0.5663 0.0155 Analysis of variance table for regression model: Source DF SS MS F-stat P-value Model 1 23.204287 23.204287 24.899859 0.0155 Error 3 2.795713 0.93190435 Total 26 Predicted values: X value Pred. Y s.e.(Pred. y) 95% C.I. for mean 95% P.I. for new 130 12.26028 0.86489939 (9.5077841, 15.012776) (8.135413, 16.385147)

Hence,

Step - 1: Slope = 0.113

Step - 2: y - Intercept = -2.383

Step - 3: Estimated value = 12.260

Step - 4: Change in dependent variable = b1 = 0.113

Step - 5: Error prediction = 13 - 12.260 = 0.740

Step - 6: Coefficient of determination = 0.892