(b) Finally, the researcher is interested in examining the regression model for knowledge, attitude and practices towards the COFLU-20. The following model was developed to forecast individual practices towards COFLU-20 using knowledge and attitude scores. P = a + B K + 3 A where P = Practice towards COFLU-20 score K = Knowledge towards COFLU-20 score A = Attitude towards COFLU-20 score The data are processed using MINITAB and the output in Exhibit 1 below was obtained: Exhibit 1 The regression equation is *** Predictor Constant SE 0.462 t-ratio 10.282 Coef 4.755 Knowledge Attitude 0.8 0.024 0.039 2.055 0.041 0.6 0.393 0.695 R-sq = 81.5% Analysis of Variance SOURCE Regression Error MS 19.03 8.333 DF 2 38.06 2.284 0.104 297 2474.887 Total 299 2512.947 ) Identify the dependent variable(s) and the independent variable(s). (ii) Is ð significant? Show proof of the testing process used to arrive at your decision. State what this means in terms of attitude and practices. (ii) What does the value of R-sq indicate? Comment on the value of R-sq.

(b) Finally, the researcher is interested in examining the regression model for knowledge, attitude and practices towards the COFLU-20. The following model was developed to forecast individual practices towards COFLU-20 using knowledge and attitude scores. P = a + B K + 3 A where P = Practice towards COFLU-20 score K = Knowledge towards COFLU-20 score A = Attitude towards COFLU-20 score The data are processed using MINITAB and the output in Exhibit 1 below was obtained: Exhibit 1 The regression equation is *** Predictor Constant SE 0.462 t-ratio 10.282 Coef 4.755 Knowledge Attitude 0.8 0.024 0.039 2.055 0.041 0.6 0.393 0.695 R-sq = 81.5% Analysis of Variance SOURCE Regression Error MS 19.03 8.333 DF 2 38.06 2.284 0.104 297 2474.887 Total 299 2512.947 ) Identify the dependent variable(s) and the independent variable(s). (ii) Is ð significant? Show proof of the testing process used to arrive at your decision. State what this means in terms of attitude and practices. (ii) What does the value of R-sq indicate? Comment on the value of R-sq.

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?
Suppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 What is the predicted area of a kitchen with a height of 96 inches and 10 cabinets? Report your answer to 1 decimal place. square feet
Suppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 10 Question 10 This is not a form; we suggest that you use the browse mode and read all parts of the question carefully. Which of the following is the correct interpretation of the coefficient for Cabinets? For a kitchen with a given ceiling height, the average number of cabinets…
Suppose that a kitchen cabinet warehouse company would like to be able to predict the area of a customer’s kitchen using the number of cabinets and the kitchen ceiling height. To do so data is collected on the following variables from a random sample of customers: Area – area of the kitchen in square feet Height – ceiling height in the kitchen (from floor to ceiling) in inches Cabinets – number of cabinets in the kitchen Suppose that a multiple linear regression model was fit to the data and that the following output resulted: Coefficients: (Intercept)HeightCabinets Estimate-57.98771.2760.3393 Std. Error8.63820.26430.1302 t value -6.7134.8282.607 Pr(>|t|)2.75e-074.44e-050.0145 Why is the interpretation of the constant term (i.e. "intercept") not meaningful for this example? The predicted area will be negative when the number of cabinets is zero and the height of the kitchen is also zero. But we cannot have a negative area, nor a kitchen ceiling height of 0 inches.…
Jensen Tire & Auto is deciding whether to purchase a maintenance contract for its newcomputer wheel alignment and balancing machine. Managers feel that maintenance expenseshould be related to usage, and they collected the following information on weeklyusage (hours) and annual maintenance expense (in hundreds of dollars). a. Develop a scatter chart with weekly usage hours as the independent variable. Whatdoes the scatter chart indicate about the relationship between weekly usage and annualmaintenance expense?b. Use the data to develop an estimated regression equation that could be used to predictthe annual maintenance expense for a given number of hours of weekly usage. Whatis the estimated regression model? c. Test whether each of the regression parameters b0 and b1 is equal to zero at a 0.05level of significance. What are the correct interpretations of the estimated regressionparameters? Are these interpretations reasonable?d. How much of the variation in the sample values of…
A mail-order business selling personal computer supplies, software and hardware maintains a centralized warehouse. Management is currently examining the process of distribution from the warehouse and wants to study the factors that affect the warehouse distribution costs. Data collected over 24 random months contain the warehouse’s distribution cost (in thousands of Rands), the sales (in thousands of Rands) and the number of orders received. A multiple linear regression model was fitted to the data by using Stat1.2. Use the output to answer the questions that follow by typing only the letter of the correct option in the answer boxes. Variablesy: Warehouse Distribution Costx1: Salesx2: Number of Orders Model Fitting StatisticsR2 = 0.8504Adj R2: ? Regression Coefficients Beta Parameter Standard b Parameter Standard Estimates…