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If data set has a relationtionship that is best described by a linear model, then the residual plot will
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- The following linear regression model can be used to predict ticket sales at a popular water park. Ticket sales per hour = - 631.25 + 11.25(current temperature in °F)23) Choose the statement that best states the meaning of the slope in this context. A) The slope tells us that a one degree increase in temperature is associated with an average increase in ticket sales of 11.25 tickets. B) The slope tells us that high temperatures are causing more people to buy tickets to the water park. C) The slope tells us that if ticket sales are decreasing there must have been a drop in temperature. D) None of theseThe General Aviation Manufacturers Association has reported annual flying hours and fuel consumption for airplanes with a single, piston-driven engine as listed in file XR15057. Data are in millions of flying hours and millions of gallons of fuel, respectively. Determine the linear regression equation describing fuel consumption as a function of flying hours, then identify and interpret the slope, the coefficient of correlation, and the coefficient of determination. At the 0.05 level of significance, could the population slope and the population coefficient of correlation be zero? Determine the 95% confidence interval for the population slope Year Hours Gallons 1992 18400000 199100000 1993 17000000 184200000 1994 16400000 177200000 1995 17800000 192600000 1996 17600000 188400000 1997 18300000 196300000Independent variable data is listed in cells B2 through B100, and dependent variable data is in cells C2 through C100. Which spreadsheet function would calculate the slope of a linear regression model of this data? Group of answer choices =SLOPE(B2:B100,C2:C100) =SLOPE(C2:C100,B2:B100) =SLOPE(B2,C2) =SLOPE(C2,C100,B2,B100)
- The Ipod Touch has been out for several years now and a lot of data has been collected. There is a functional relationship between the Price of an IPod Touch and Weekly Demand. Below is a table of data that have been collected Price P ($) Weekly Demand S (1,000s) 150 212 170 207 190 193 210 186 230 176 250 174 A.. Find the linear model that best fits this data using regression and enter the model below (for entry round the slope value to nearest 0.01 and constant parameter to nearest 1) T(p) = %3D Now answer these two questions: B.. What does the model predict will be the weekly demand if the price of an ipod touch is $231 ? (nearest 100) C.. According to the model at what should the price be set in order to have a weekly demand of 180,100 ipod Touches? $ (nearest $1)Several months ago, John O'Hagan investigated the effect on the popularity of OHaganBooks.com of placing banner ads at well-known Internet portals. When OHagan Books.com actually went ahead and increased Internet advertising from $5,000 per month to $6,000 per month it was noticed that the number of new visits increased from an estimated 2,030 per day to 2,090 per day. Use this information to construct a linear model giving the average number v of new visits per day as a function of the monthly advertising expenditure c. (a) What is the model? v(c) = (b) Based on the model, how many new visits per day could be anticipated if OHaganBooks.com budgets $7,000 per month for Internet advertising? visits (c) The goal is to eventually increase the number of new visits to 2,600 per day. Based on the model, how much should be spent on Internet advertising to accomplish this? $The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through c Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs = 247733.3 +(43.2000) x Billable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) b. Interpret the coefficients of your regression model. Specifically, what does the fixed component of the model mean to the consulting firm? Interpret the fixed term, bo. if appropriate. Choose the correct answer below. OA. The value of by is the predicted overhead costs for 0 billable hours. OB. For each increase of 1 unit in overhead costs, the predicted billable hours are estimated to increase by bo OC. It is not appropriate to interpret by. because its value is the predicted…
- 9 students were surveyed to see what their age is and what their income level is. Find the equation of the line using linear regression. We want to predict their age using their income. age 18 24 38 22 19 35 28 19 27 income 456 786 835 855 645 244 587 1400 975 Just a side note, the 19 year old is making 1400, would be considered an outlier since they are making way more than everyone else. (y=-.0061x+34.9874 4 decimals) y=30.3709-.0064A biscuit production manager wants to investigate the linear relationship between the number of items produced and the production cost. To pursue his/her objective, the manager recorded the data on the number of items produced per day and the production cost per day (in thousands of Malaysian Ringgit) as shown in Table 3 Table 3 Days 1 2 4 6. 7 8 10 11 Number of items, (x) 26 67 86 17 10 44 53 40 77 80 20 20 Production cost, (y) 21 60 69 47 50 | 98 39 55 85 104 37 20 a) Name the TWo (2) most popular correlation coefficients. OPearson Oz-table OT-table Ochi-square Ospearman b) Calculate the correlation coefficient, r. ху x2 y2 26 21 676 44 60 2640 1936 3600 53 69 3657 2809 4761 47 1880 2209 77 50 3850 5929 2500 80 98 7840 6400 9604 20 39 780 400 1521 20 55 1100 400 3025 67 5695 4489 7225 86 104 8944 7396 10816 17 37 629 289 1369 10 20 200 100 400 E y² = Σχ ΣΥ- Σχy- Ex? = || || **Answer should be up to 4 decimal place (dp) r = c) Based on the correlation coefficient, robtained, make a…The I-85 Carpet Outlet wants to develop a means to forecastits carpet sales. The store manager believes that the store’s sales are directly related to the number of new housing starts in town. The manager has gathered data from county records of monthly house construction permits and from store records on monthly sales. These data are as follows: a. Develop a linear regression model for this data and forecast carpet sales if 25 construction permits for new homes are filed. b. Determine the strength of the causal relationship be- tween monthly sales and new home construction using correlation. Monthly Carpet Sales Monthly Construction(1000s yd) Permits5 1712 306 125 14
- The registrar at State University believes that decreases in thenumber of freshman applications that have been experiencedare directly related to tuition increases. They have collectedthe following enrollment and tuition data for the past decade: a. Develop a linear regression model for these data andforecast the number of applications for State Universityif tuition increases to $10,000 per year and if tuition islowered to $7000 per year.b. Determine the strength of the linear relationship betweenfreshman applications and tuition using correlation. c. Describe the various planning decisions for State Univer-sity that would be affected by the forecast for freshman applications.A national homebuilder builds single-family homes and condominium-style townhouses. The accompanying dataset provides information on the selling price, lot cost, and type of home for closings during one month. Complete parts a through c. E Click the icon to view the house sales data. House sales data a. Develop a multiple regression model for sales price as a function of lot cost and type of home without any interaction term. Create a dummy variable named "Townhouse", where it is equal to 1 when Type = "Townhouse" and 0 otherwise. Determine the coefficients of the regression equation. Туре Townhouse Sales Price Lot Cost Sales Price = 108726 + ( 3.68 )• Lot Cost + ( - 75063 )• Townhouse $114,740 $138,530 $21,700 $26,550 Single Family Townhouse Single Family Townhouse (Round the constant and coefficient of Townhouse to the nearest integer as needed. Round all other values to two decimal places as needed.) $149,905 $172.000 $25,550 $26,200 b. Determine if an interaction exists between lot…The managing director of a consulting group has the accompanying monthly data on total overhead costs and professional labor hours to bill to clients. Complete parts a through o. Click the icon to view the monthly data. a. Develop a simple linear regression model between billable hours and overhead costs. Overhead Costs OxBillable Hours (Round the constant to one decimal place as needed. Round the coefficient to four decimal places as needed. Do not include the $ symbol in your answers.) Monthly Overhead Costs and Billable Hours Data Overhead Costs $385,000 Billable Hours 3,000 $425,000 4,000 $445.000 5,000 $497,000 6,000 $570,000 7,000 $590,000 8,000