4. The table shows a company's yearly profit beginning Time Since 2004 (years) Profit 12.3 11.9 (hundred thousands of dollars) Use a quadratic regression to predict the company's a. 469000 b. 705000 C. 700000 d. 674000
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- Oregon Fiber Board makes roof liners for the automotiveindustry. The manufacturing manager is concerned aboutproduct quality. She suspects that one particular failure, tears in the fabric, is related to production-run size. An assistantgathers the following data from production records: a. Draw a scatter diagram for these data.b. Does there appear to be a relationship between run sizeand percent failures? What implications does this datahave for Oregon Fiber Board’s business?Table 8 Amounts of New Solar Power Installed in the United States Amount of New Solar Power Installed Year (megawatts) 2006 2007 105 160 2008 290 2009 435 2010 878 2011 1891 3300 2012 Source: GTM Research If the model is given by: y 2.73(1.80)*, what is the growth rate? O the growth rate is 273%. O The growth rate is 80%. O can not be determined from the equation. O The growth rate is 73% O The growth rate is 180%. 99+ a5. Among important factors that affecting the price of land lot are size, number of mature trees and distance to the lake. Using data for 60 recently sold land lots are shown below: B 1 SUMMARY OUTPUT 2 3. Regression Statistics 4 Multiple R 5 R Square 6 Adjusted R Square 7 Standard Error 0.4924 0.2425 0.2019 40.24 8 Observations 60 9. 10 ANOVA Significance F 5.97 11 df S MS 9676.6 0.0013 12 Regression 13 Residual 3 29,030 90,694 56 1619.5 14 Total 59 119,724 15 16 Coefficients Standard Error t Stat P-value 0.0331 0.2156 17 Intercept 51.39 23.52 2.19 18 Lot size 0.700 0.559 1.25 19 Trees 0.679 0.229 2.96 0.0045 20 Distance -0.378 0.195 -1.94 0.0577 a) Write the regression equation b) What is the standard error of estimate? Interpret its value. c) What is the coefficient of determination? Interpret its value. d) What is the adjusted coefficient of determination? Interpret its value. e) Test the validity of the model. f) Interpret each of the coefficients. g) Test at 5% level of…
- d. If the director used these 4 weeks of data to create a linear regression, what does that linear regression formula suggest for this week's forecast of employee appointments? What does the regression analysis suggest in general about employee appointments for Director Very Busy?hello i just wanna know if my answer to this question is correct or wrong: Consider five years of monthly pro fit for a company C) Discuss whether a simple exponential smoothing model works well with this data or not. Month Sales Jan-16 747 Feb-16 697 Mar-16 1014 Apr-16 1126 May-16 1105 Jun-16 1450 Jul-16 1639 Aug-16 1711 Sep-16 1307 Oct-16 1223 Nov-16 975 Dec-16 953 Jan-17 1024 Feb-17 928 Mar-17 1442 Apr-17 1371 May-17 1536 Jun-17 2004 Jul-17 1854 Aug-17 1951 Sep-17 1516 Oct-17 1642 Nov-17 1166 Dec-17 1106 Jan-18 1189 Feb-18 1209 Mar-18 1754 Apr-18 1843 May-18 1769 Jun-18 2207 Jul-18 2471 Aug-18 2288 Sep-18 1867 Oct-18 1980 Nov-18 1418 Dec-18 1333 Jan-19 1333 Feb-19 1370 Mar-19 2142 Apr-19 2138 May-19 2078 Jun-19 2960 Jul-19 2616 Aug-19 2861 Sep-19 2237 Oct-19 2225 Nov-19 1590 Dec-19 1659 Jan-20 1613 Feb-20 1605 Mar-20 2349 Apr-20 2468 May-20 2532 Jun-20 3127 Jul-20 3288 Aug-20 3285 Sep-20 2485 Oct-20 2723 Nov-20 1835 Dec-20 1894 here is my answer: Assessing the Applicability of…Write is details about the regression analysis?
- I got the graph correct, but what am I doing wrong to get the two equA company sets different prices for a particular DVD system in eight different regions of the country. The accompanying table shows the numbers of units sold and the corresponding prices (in dollars). Sales 420 380 350 400 440 380 450 420 Price 104 195 148 204 96 256 141 109a. Graph these data, and estimate the linear regression of sales on price. b. What effect would you expect a $50 increase in price to have on sales?explain the graphs? Please answer fast.
