1415 Note: you can add as many rows or columns to the data presented below as you find necessary.166717181920212223242526272829303132333435201120122013201420152016201720182019202020212022Arithmetic Average Growth RateGeometric Average Growth RateTrendTotal Assets in $ millionNVIDIATesla7131,1142,4165,8308,06722,66428,65529,74034,30952,14862,13182,3384,4955,5526,4127,2507,2017,3709,84111,24113,29217,31528,79144,187Year202220212020201920182017201620152014201320122011Arithmetic Average Growth RateGeometric Average Growth RateTrendRevenue in S millionsTesla NVIDIA81,462 26,91453,82316,67531,536 10,91824,57811,71621,4619,71411,7596,9107,0005,0104,0464,6823,1984,1302,0134.2804132043,9973,543

We will use the following formulas: The rate of change of assets each year is calculated using the…

Answered: Note: you can add as many rows or…

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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The Toro Cutlery Company has collected monthly sales information below! MONTH January February March April SALES 22,000 21,000 34,000 120,000 Forecast (January, 3-month MA) Forecast (January, 4-month MA): Forecast (January, 5-month MA): SALES 102,000 33,000 MONTH MONTH SALES May September 28,000 June 76,000 October November July 84,000 79,000 August 46,000 December 87,000 The company is examining two forecasting methods, moving average and exponential smoothing for forecasting sales a. What will the forecast be for January the following year using a three, four, and five-month moving averages? Do not round intermediate calculations. Round your answers to the nearest whole number b. What will the forecast be for January the following year using exponential smoothing with a 0.77 Assume the forecast for February this year is 22,000. Do not round intermediate calculations. Round your answer to the nearest whole number
Month January February March April May June July August September October November December Year 2016 2017 2018 $1,468 $1,386 $1,271 727 719 709 778 713 687 691 707 729 781 704 669 1,374 997 689 703 709 734 710 787 727 701 1,524 1,364 1,064 986 715 741 742 768 1,256 1,157 1,259 Click here for the Excel Data File 2019 $1,144 666 685 c. Which forecasting model is appropriate based on the data for the total U.S. bookstore sales? Appropriate model Regression analysis d. Evaluate a seasonally adjusted trend forecasting model. What is the MAD? (Round your answers to 4 decimal places.)
The table below contains real data for the first two decades of AIDS reporting. Year # AIDS cases diagnosed # AIDS deaths Pre-1981 91 29 1981 319 121 1982 1,170 453 1983 3,076 1,482 1984 6,240 3,466 1985 11,776 6,878 1986 19,032 11,987 1987 28,564 16,162 1988 35,447 20,868 1989 42,674 27,591 1990 48,634 31,335 1991 59,660 36,560 1992 78,530 41,055 1993 78,834 44,730 1994 71,874 49,095 1995 68,505 49,456 1996 59,347 38,510 1997 47,149 20,736 1998 38,393 19,005 1999 25,174 18,454 2000 25,522 17,347 2001 25,643 17,402 2002 26,464 16,371 Total 802,118 489,093 Graph "year" versus "# AIDS cases diagnosed" (plot the scatter plot). Do not include pre-1981 data. Perform linear regression. Write the equations. (Round your answers to the nearest whole number. Round r to four decimal places.) (a) Linear Equation: 9 - (b) a = (c) b= (d) (e) n-
1937 -3.8 1938 3.3 1939 4.6 1940 4.5 1941 5.4 1942 2.9 1943 -0.6 1944 4.1 1945 4.8 1946 4.4 1947 0.5 1948 3.4 1949 -1.4 1950 -6.3 1951 2.5 1952 1.7 1953 5.9 1954 0.5 1955 3.6 1956 3 1957 -1.1 1958 6 1959 3.8 1960 2.7 1961 4.9 1962 2.9 1963 0.7 1964 4.5 1965 2.1 1966 2.9 1967 4.5 1968 3.8 1969 -2.9 1970 3.1 1971 2.2 1972 0.7 1973 2.3 1974 2.6 1975 2.4 1976 4.3 1977 2.3 1978 3.5 1979 0.2 1980 0.5 1981 5.5 1982 1.9 1983 6.3 1984 4.4 1985 1.5 1986 6.1 1987 4.4 1988 3.5 1989 3.5 1990 4.4 1991 1.6 1992 5.8 1993 -0.4 1994 6.3 1995 4.5 1996 2.9 1997 3.9 1998 4.5 1999 5 2000 3.5 2001 5.1 2002 4.2 2003 6.4 2004 4.1 2005 3.7 2006 6.3 2007 3 2008 2.8 2009 2.1 2010 7.2 2011 4.2 2012 3.6 2013 2.8 2014 4.4 2015 5.6 2016 4.7 2017 1.9 2018 5.4 2019 5.8 Find question 12
Compute Laspeyre's, Paasche's, Fisher's and Marshall-Edgeworth's Index Numbers from the following data. Item Base Year Current Year Price ( $ ) Quantity Price ( $ ) Quantity 5 25 6 30 B 3 8 4 10 2 10 3 8 10 4 3 5
I. The Department of Agriculture obtained the following data representing the one week growth in centimeters of 30 newly planted corn plants.
Walmart predicted the following end-of-year earnings from 2003 - 2012 in billions of dollars (9.5, 9.8, 10.2, 10.7, 10.5, 11.0, 12.1, 14.7, 16.3, 18.7). Their actual end-of- year earnings for the same years are as follows: 9.1, 9.2, 10.6, 10.3, 9.9, 10.4, 11.6, 11.8, 13.1, 22.7). In testing the claim that the mean predicted value is the same as the mean actual value, which p-value is correct? 0.228 0.456 0.779 0.05 4
Piedmont Park certainly notices that its attendance is seasonal. They've collected data for the last three years (attendance in thousands) with the data shown below. What would be the forecast for Winter 2024 (to two decimal places) before adjusting for seasonality? Quarter 2021 2022 2023 Winter 100 102 106 Spring 160 170 180 Summer 250 280 260 Fall 180 190 192 Selected Answer: 102.67
Year 1990 1995 2000 2005 Quantity/Price Quantity Price Quantity Price Quantity Price Quantity Price Good 1 98 104 28 137 35 Good 2 45 39 38 60 43 74 55 Good 3 89 73 20 105 24 Total value 3573 4287 6952 11385 Answer the following questions. Round your answers to the nearest first decimal. a. Compute the 2000 Laspeyres quantity index base 100 = 1990. 122.3 b. Compute the 1990 Laspeyres price index base 100 = 2005. 49.2 c. Compute the 2005 Paasche quantity index base 100 = 1995. 154.0 d. Compute the 1995 Paasche price index base 100 = 1990. 131.4 e. Compute the 2005 Fisher price index base 100 = 1995. 170.44 f. Compute the 2000 chained Fisher price index base 100 = 1990. 170.0
You collect data of average annual returns for Amazon Stock and Microsoft Stock and make the following table: (This data can be copied into Excel.) Year Amazon Return Microsoft Return 2013 0.5896 0.1221 2014 -0.2218 0.2416 2015 1.1778 0.1944 2016 0.1095 0.1200 2017 0.5596 0.3766 2018 0.2843 0.1874 2019 0.3216 0.5526 You use this data to answer the research question: are true population Amazon Returns greater than true population Microsoft Returns?
The following table shows inflation rates for several decades into 2020 dollars. Time span 1980-2020 1990-2020 2000-2020 2010-2020 Inflation 232% 102% 53% 19% The following table shows the nominal (unadjusted) prices for gold over several years. Complete the table showing gold prices in constant 2020 dollars. (Round to the nearest cent.) Show your work below the table. Year 1980 1990 2000 2010 2020 Nominal (unadjusted) price per ounce $516.92 $381.73 $273.68 $1179.25 $1636.35 Constant (adjusted) price per ounce in 2020 dollars 1a. 1980 $516.92 1b. 1990 $381.73 1c. 2000 $273.68 1d. 2010 $1179.25 1e. 2020 $1636.35 It is not necessary to adjust the 2020 price, but you must still fill in…
Consider the monthly unit sales for 2019, the company's full year 2020 forecast, and year-to-date monthly unit sales for 2020. 2020 Company Forecast 2020 YTD 2019 Month Actual Actual Jan 104 101 100 Feb 92 93 103 Mar 105 109 101 Apr 90 101 103 May 95 95 100 Jun 97 99 106 Jul 99 100 102 Aug 101 98 100 Sep 104 106 108 Oct 98 101 101 Nov 91 95 Dec 94 95 You have been asked to revise the 2020 forecast for November. What has the mean absolute deviation been for the first ten months of 2020? Answer with one decimal point. What has the bias been for the first ten months of 2020? Answer with one decimal point. What is your forecast for November, 2020, using the Naive method? Answer as an integer.| What is the forecast for November, 2020 using a three month moving average? Answer as an Integer. What is the forecast for November, 2020 using a weighted average with welghts of 20%, 30% and 50% for August, September and October, respectively? Answer as an integer.

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