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##### Fitting a straight line to a set of data yields the following

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solution

**Question**

12.3 Fitting a straight line to a set of data yields the following;prediction line;a. Interpret the meaning of the Y intercept;b. Interpret the meaning of the slope;c. Predict the value of Y for X =6;12.7 Starbucks Coffee Co. uses a data-based approach to improving;the quality and customer satisfaction of its products.;When survey data indicated that Starbucks needed to improve;its package sealing process, an experiment was conducted (data;extracted from L. Johnson and S. Burrows, ?For Starbucks, It?s;In the Bag,? Quality Progress, March 2011, pp. 17?23) to determine;the factors in the bag-sealing equipment that might be;affecting the ease of opening the bag without tearing the inner;liner of the bag. One factor that could affect the rating of the;ability of the bag to resist tears was the plate gap on the bagsealing;equipment. Data was collected on 19 bags in which the;plate gap was varied. The results are stored in Starbucks.;a. Construct a scatter plot.;b. Assuming a linear relationship, use the least-squares;method to determine the regression coefficients b0 and b1;c. Interpret the meaning of the slope, b1, in this problem.;d. Predict the tear rating when the plate gap is equal to 0.;Tear Viscosity Pressure Plate Gap;0.00 350.00 180.00 0.00;0.00 350.00 170.00 0.00;0.45 319.00 186.00 1.80;0.85 380.00 174.00 1.80;0.35 350.00 180.00 0.00;0.30 300.00 180.00 0.00;0.70 400.00 180.00 0.00;1.90 350.00 190.00 0.00;0.25 350.00 180.00 0.00;0.10 319.00 186.00 -1.80;0.15 380.00 186.00 -1.80;3.90 350.00 180.00 3.00;0.00 380.00 174.00 -1.80;0.55 350.00 180.00 0.00;0.00 350.00 180.00 -3.00;0.05 319.00 174.00 -1.80;0.40 319.00 174.00 1.80;4.30 380.00 186.00 1.80;0.00 350.00 180.00 0.00;12.9 An agent for a residential real estate company has the;business objective of developing more accurate estimates of;the monthly rental cost for apartments. Toward that goal, the;agent would like to use the size of an apartment, as defined;by square footage to predict the monthly rental cost. The;agent selects a sample of 25 apartments in a particular residential;neighborhood and collects the following data (stored in RENT).;Rent Size;950 850;1600 1450;1200 1085;1500 1232;950 718;1700 1485;1650 1136;935 726;875 700;1150 956;1400 1100;1650 1285;2300 1985;1800 1369;1400 1175;1450 1225;1100 1245;1700 1259;1200 1150;1150 896;1600 1361;1650 1040;1200 755;800 1000;1750 1200;12.19 In Problem 12.7 on page 441, you used the plate gap;on the bag-sealing equipment to predict the tear rating of a;bag of coffee (stored in). Using the results of that;problem;a. determine the coefficient of determination, and interpret;its meaning.;b. determine the standard error of the estimate.;c. How useful do you think this regression model is for;predicting the tear rating based on the plate gap in the;bag-sealing equipment?;12.21 In Problem 12.9 on page 442, an agent for a real;estate company wanted to predict the monthly rent for apartments;based on the size of the apartment (stored in).;Using the results of that problem;a. determine the coefficient of determination, and interpret;its meaning.;b. determine the standard error of the estimate.;c. How useful do you think this regression model is for predicting;the monthly rent?;d. Can you think of other variables that might explain the;variation in monthly rent?

Paper#67396 | Written in 18-Jul-2015

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