Statistics students in Oxnard College sampled 10 textbooks in the Condor bookstore and recorded the number of pagesin each textbook and its cost. The bivariate data are shown below:Number of Pages (x)Cost(y)90788.6384588.0585.6192920237.1869568.5531045.920521.4536844.1248.4738388888.92A student calculates a linear model(Please show your answers to two decimal places)X.Use the model to estimate the cost when number of pages is 352.Cost $(Please show your answer to 2 decimal places.)Enter an integer or decimal number [more..]

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Asked Oct 8, 2019
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Statistics students in Oxnard College sampled 10 textbooks in the Condor bookstore and recorded the number of pages
in each textbook and its cost. The bivariate data are shown below:
Number of Pages (x)
Cost(y)
907
88.63
845
88.05
85.61
929
202
37.18
695
68.55
310
45.9
205
21.45
368
44.12
48.47
383
888
88.92
A student calculates a linear model
(Please show your answers to two decimal places)
X.
Use the model to estimate the cost when number of pages is 352.
Cost $
(Please show your answer to 2 decimal places.)
Enter an integer or decimal number [more..]
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Statistics students in Oxnard College sampled 10 textbooks in the Condor bookstore and recorded the number of pages in each textbook and its cost. The bivariate data are shown below: Number of Pages (x) Cost(y) 907 88.63 845 88.05 85.61 929 202 37.18 695 68.55 310 45.9 205 21.45 368 44.12 48.47 383 888 88.92 A student calculates a linear model (Please show your answers to two decimal places) X. Use the model to estimate the cost when number of pages is 352. Cost $ (Please show your answer to 2 decimal places.) Enter an integer or decimal number [more..]

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Expert Answer

Step 1

Regression:

In order to obtain the least square regression line, first perform regression analysis on the data.

The regression analysis is conducted here by using EXCEL. The software procedure is given below:

  • Enter the data.
  • Select Data > Data Analysis > Regression> OK.
  • Enter...
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SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square 0.954792225 0.979701644 0.959815311 Standard Error 5.366834655 Observations 10 ANOVA Significance F 7.24775E-07 df SS MS F 1 Regression 5503.683846 5503.683846 191.0807984 Residual 8 230.4233137 28.80291422 Total 9 5734.10716 Lower 95.0 % Coefficlents Standard Error t Stat P-value Upper 95% Upper 95.0 % Lower 95% Intercept 15.47576645 3.74920806 4.127742768 0.003308723 6.830077164 24.12145574 6.830077164 24.12145574 X Variable 1 0.080621482 0.005832332 13.82319784 7.24775E-07 0.0671721 0.094070864 0.0671721 0.094070864

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