2010 Price Quantity 100 2016 Price QuantitY 113 55 85 10 se.24 50.32 0.29 0.34 1.04 0.64 0.43 50 asket) 2.79 0.91 1.96 10 Click here forthe Excel Data Fle mple price indexes. (Round your answers to 2 decimal places) Simple index
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- Jsjxk kkepls help understand how to draw graphsMOER The table below shows how supply and demand Price ($/gal) Demand (million of gal.) 1 1.2 790 700 1.4 640 1.6 580 1.95 497 2.2 450 2.4 430 2.6 420 2.8 390 3 360 Note: there is some randomization in the above data to account for price fluctuations. Make sure to check that you input the correct data in your device. Perform the following work • Assume that Supply has a quadratic relationship with the price. Find this relationship (the help buttons contain an article to compute trend-lines in Excel): -21.935p² + 207.365p+339.085 Round your answer to 3 decimal places S(p) ● D(p): = 1.53 • Assume that the Demand has a quadratic relationship with the price. Find this relationship (the help button links to an article to compute trend-lines in Excel): 85.561p² - 543.789p + 1236.729 Round your answer to 3 decimal places Video Solve | Sn... of gasoliine vary depending on the price: Supply (million of gal.) 511 550 600 641 660 680 700 720 735 786 605 - • Use the trendlines to find the price…
- Suppose seafood price and quantity data for the years 2000 and 2009 follow. Use 2000 as the base period.Seafood 2000 Qty. (lb) | 2000 Price ($/lb) | 2009 Price ($/lb)Halibut 75,090 1.91 2.33Lobster 83,080 3.72 3.09Tuna 50,779 1.87 1.97(a)Compute a price relative for each type of seafood. (Round your answers to one decimal place.)Seafood Price RelativeHalibut 122.0 Lobster _________ Tuna 105.3 (b)Compute a weighted aggregate price index for the seafood catch. (Round your answer to one decimal place.)I2009 = ___________ Comment on the change in seafood prices over the nine-year period. (Enter your percentage as a positive value. Round your answer to one decimal place.)Seafood prices have decreased by ______ % over the 9-year period according to the index.I Consider the demand for trading cards listed below. Month Demand Jan. 51,000 48,000 Feb. March 55,000 April May 58,000 66,000 June 69,000 80,000 July Aug. 95,000 Use Excel to prepare a forecast for September, October, and November using linear regression Print out the sheet of results, as well as a sheet containing the formulas that you used ( can be used to toggle between displaying values and displaying formulas or you can click on Formulas>Formula Auditing→Show Formulas.) and for the cars is 16.000TABLE 12.1 | Two Stage Least Squares Estimates of the Demand for Cigarettes Using Panel Data for 48 U.S. States Dependent variable: In(Qfte) – In(Qfte) cigarettes Regressor (1) (2) (3) In(Peisarettes) - In(Pçigarettes -0.94** -1.34** -1.20** i,1995 i,1985 (0.21) (0.23) (0.20) In(Inc;1995) – In(Inc;1985) 0.53 (0.34) 0.43 (0.30) 0.46 (0.31) Intercept -0.12 -0.02 -0.05 (0.07) (0.07) (0.06) Both sales tax and Instrumental variable(s) Sales tax Cigarette-specific tax cigarette-specific tax First-stage F-statistic 33.70 107.20 88.60 Overidentifying restrictions J-test and p-value 4.93 (0.026) These regressions were estimated using data for 48 U.S. states (48 observations on the 10-year differences). The data are described in Appendix 12.1. The J-test of overidentifying restrictions is described in Key Concept 12.6 (its p-value is given in parentheses), and the first-stage F-statistic is described in Key Concept 12.5. Individual coefficients are statistically significant at the *5%…
- Ypsilanti Market Research conducted a survey to find out whether people who earn more money purchase more expensive goods. The following graph indicates the relationship between income the survey subjects earned and the price of the car that they purchased. PRICE (Thousands of dollars per car) 50 45 40 5 0 0 10 20 30 40 50 60 80 70 INCOME (Thousands of dollars per year) 90 100Ypsilanti Market Research conducted a survey to find out whether people who earn more money purchase more expensive goods. The following graph indicates the relationship between income the survey subjects earned and the price of the home that they purchased. PRICE (Thousands of dollars per home) 500 450 400 350 300 250 200 150 100 50 L 0 10 20 30 40 50 60 70 80 INCOME (Thousands of dollars per year) 90 100please help me 1, 2 and 3
- Please Use IRR% formula not the chart Thank youEconomics jj Consider the partial data set in the table represents online hours spent shopping by age and income. Using the min-max transformation to normalize Income, what is the average standard deviation of Income for the chart provided? Use the min-max transformation to normalize the observations for Income spent online. Age ID 2,201 2,202 2,203 2,204 2,205 2,206 Income 57,000 57,000 54,000 17,000 37,000 45,000 Multiple Choice 1.000 0.6875 51 48 45 35 33 31 Online Hours S459N4 2How was 1.40331 calculated?