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Mathematical Methods in the Physical Sciences
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- Please answer exercise 11.2.10 and 11.4.1 stepwisearrow_forwardTo help consumers in purchasing a laptop computef, Consumer Reports calculates an overall test score for each computer tested based upon rating factors such as ergonomics, portability, performance, display, and battery life. Higher overall scores indicate better test results. The following data show the average retail price and the overall score for ten 13-inch models (Consumer Reports website, October 25, 2012). Price Overall Brand & Model Score Samsung Ultrabook NP900X3C-A01US 1250 83 Apple MacBook Air MC965LL/A 1300 83 Apple MacBook Air MD231LL/A 1200 82 HP ENVY 13-2050nr Spectre XT 950 79 Sony VAIO SVS13112FXB 800 77 Acer Aspire S5-391-9880 Ultrabook 1200 74 Apple MacBook Pro MD101LL/A 1200 74 Apple MacBook Pro MD313LL/A 1000 73 Dell Inspiron 113Z-6591SLV 700 67 600 63 Samsung NP535U3C-A01US a. Develop a scatter diagram with price as the independent variable. b. What does the scatter diagram developed in part (a) indicate about the relationship between the two variables? c. Use the…arrow_forwardPlease answer exercises 11.4.8 and 11.4.10 Stepwisearrow_forward
- Please answer exercises 11.4.4 and 11.4.5 Stepwisearrow_forwardData on advertising expenditures and revenue (in thousands of dollars) for the Four Sea- sons Restaurant follow, Advertising Expenditures Revenue 124 19 32 44 6 40 10 52 14 20 53 54 a. Let x equal advertising expenditures and y equal revenue. Use the method of least squares to develop a straight line approximation of the relationship between the two variables. b. Test whether revenue and advertising expenditures are related at a .05 level of significance. - C. Prepare a residual plot of yŷ versus ŷ. Use the result from part (a) to obtain the values of ŷ. d. What conclusions can you draw from residual analysis? Should this model be used, or should we look for a better one?arrow_forwardPlease answer exercises 11.2.7 and 11.2.8 Stepwisearrow_forward
- In a manufacturing process the assembly line speed (feet per minute) was thought to af- fect the number of defective parts found during the inspection process. To test this theory, managers devised a situation in which the same batch of parts was inspected visually at a variety of line speeds. They collected the following data. Line Speed 20 Number of Defective Parts Found 21 20 19 40 *** 40 15 30 16 60 14 17 a. Develop the estimated regression equation that relates line speed to the number of defective parts found. b. At a .05 level of significance, determine whether line speed and number of defective parts found are related. C. Did the estimated regression equation provide a good fit to the data? d. Develop a 95% confidence interval to predict the mean number of defective parts for a line speed of 50 feet per minute.arrow_forwardPlease answer exercise 11.4.11 Stepwisearrow_forwardIn exercise 12, the following data on x = average daily hotel room rate and y = amount spent on entertainment (The Wall Street Journal, August 18, 2011) lead to the estimated regression equation ŷ = 17.49 + 1.0334x. For these data SSE = 1541.4. - Room Rate Entertainment City ($) ($) Boston 148 161 Denver 96 105 Nashville 91 101 New Orleans 110 142 Phoenix 90 100 San Diego 102 120 San Francisco 136 167 San Jose 90 140 Tampa 82 98 a. Predict the amount spent on entertainment for a particular city that has a daily room rate of $89. b. Develop a 95% confidence interval for the mean amount spent on entertainment for C. all cities that have a daily room rate of $89. The average room rate in Chicago is $128. Develop a 95% prediction interval for the amount spent on entertainment in Chicago.arrow_forward
- Please answer exercises 11.4.6 and 11.4.7 Stepwisearrow_forwardAn important application of regression analysis in accounting is in the estimation of cost. By collecting data on volume and cost and using the least squares method to develop an estimated regression equation relating volume and cost, an accountant can estimate the cost associated with a particular manufacturing volume. Consider the following sample of production volumes and total cost data for a manufacturing operation. Production Volume (units) 400 Total Cost ($) 450 550 600 700 750 4000 5000 5400 5900 6400 7000 a. Use these data to develop an estimated regression equation that could be used to predict the total cost for a given production volume. b. What is the variable cost per unit produced? c. Compute the coefficient of determination. What percentage of the variation in total cost can be explained by production volume? d. The company's production schedule shows 500 units must be produced next month. Predict the total cost for this operation?arrow_forwardPlease answer exercises 11.4.2 and 11.4.3 Stepwisearrow_forward
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