A new business, CoolIT, sells items to keep you cool when outside. Its products include coolers, generators, floats, and other water accessories designed to beat the heat. CoolIT has been spending money on innovative advertising in hopes of increasing its sales revenue. A CoolIT business analyst ran a regression using 36 months of data using the Excel Data Analysis Toolpak. The output is shown below. What is the slope of the line?
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- Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.The owner of a restaurant in Bloomington, Indiana, has recorded sales data for the past 19 years. He has also recorded data on potentially relevant variables. The data are listed in the file P13_17.xlsx. a. Estimate a simple regression equation involving annual sales (the dependent variable) and the size of the population residing within 10 miles of the restaurant (the explanatory variable). Interpret R-square for this regression. b. Add another explanatory variableannual advertising expendituresto the regression equation in part a. Estimate and interpret this expanded equation. How does the R-square value for this multiple regression equation compare to that of the simple regression equation estimated in part a? Explain any difference between the two R-square values. How can you use the adjusted R-squares for a comparison of the two equations? c. Add one more explanatory variable to the multiple regression equation estimated in part b. In particular, estimate and interpret the coefficients of a multiple regression equation that includes the previous years advertising expenditure. How does the inclusion of this third explanatory variable affect the R-square, compared to the corresponding values for the equation of part b? Explain any changes in this value. What does the adjusted R-square for the new equation tell you?Management of a home appliance store wants to understand the growth pattern of the monthly sales of a new technology device over the past two years. The managers have recorded the relevant data in the file P13_05.xlsx. Have the sales of this device been growing linearly over the past 24 months? By examining the results of a linear trend line, explain why or why not.
- Applied Statistics for Engineers. Answer D-E onlyGive quality answer No handwritten solution Answer all parts You get up vote for sure.After graduation, you take a position at Top-Slice, a well-known manufacturer of golf balls. One of your duties is to forecast monthly demand for golf balls. Using the following data, you developed a regression model that expresses monthly sales as a function of average temperature for the month: Click the icon to view the additional data. a. Show how the â and ɓ values of - 337.0 and 88.9 were calculated. Calculate the slope coefficient, ɓ (enter your responses as whole numbers). (755)(63110) 4252000 Б 12 = 88.9 (755) 50665 12 Monthly sales - 337.0+88.9 × (average temperature) Calculate the intercept term, â (enter your responses rounded to one decimal place). â= 5259.2 -88.9 × 62.92 = - 337.0 b. Use the regression forecasting model to forecast total golf ball sales for June and July 2018. Average temperatures are expected to be 73 degrees in June and 82 degrees in July. The forecast of total golf ball sales for June 2018 is (Enter your response rounded to the nearest whole number.)…
- Please help with correct answers in details: step by step as last submission were given incorrect answers A statistical program is recommended. The quarterly sales data (number of copies sold) for a college textbook over the past three years follow. Quarter Year 1 Year 2 Year 3 1 1,690 1,800 1,850 2 940 900 1,100 3 2,625 2,900 2,930 4 2,500 2,360 2,615year quarterly sales (000 units) Q1 Q2 Q3 Q4 2016 1300 1500 1200 2000 2017 1600 1800 1100 2200 2018 1700 1900 1300 2300 2019 1800 2100 1400 2500 Using a simple regression analysis, determine the trend equation of the sales and use it to estimate the number of units of clothing sold throughout the fiscal year 2020. Assume that Q1 of 2016 is 1, Q2 of 2016 is 2, etc. Show all relevant cakculation detailExercise SA-5 (Algo) Least-Squares Regression (LO5-11 George Caloz & Frères, located in Grenchen, Switzerland, makes luxury custom watches in small lots. One of the company's products, a platinum diving watch, goes through an etching process. The company has recorded etching costs as follows over the last six weeks: Week 1 2 3 4 Units 14 11 16 10 12 15 78 Total Etching Cost $ 27 20 30 20 25 28 $150 For planning purposes, management would like to know the variable etching cost per unit and the total fixed etching cost per week. Exercise 5A-5 Part 2 (Algo) 2-a. Using the least-squares regression method, estimate the variable etching cost per unit and the total fixed etching cost per week. 2-b. Express these estimates in the form Y = a + bx.
- Discuss how the advantages of using simple regression could benefit the organization.Netflix decided to distribute the show "Orange is the New Black". This decision was because the show 'Weeds', performed very well on Netflix in terms of viewership and engagement. Both shows have the same writers/creative teams. Data shows that viewers enjoy shows by the same writers/creative teams. This is an example of Netflix relying upon which type of data analytics Question 4 options: a) Descriptive b) Diagnostic c) Predictive d) Prescriptive. What are the advantages and disadvantages of Regression Model, Econometric Model, Driving Indicator Models?