Q1) FIND THE FORECASTING FOR YEAR 2042, 2043, 2044YearsSheet1202020212022202320242025202620272028202920302031Home valueYear10000001200000141000016400001890000200000022000002400000268000028000003120000327000004) Find MAD, MSE AND MAPE FOR THE FOLLOWING DATAStock

The given data is, year home value 2020 1000000 2021 1200000 2022 1410000 2023 1640000…

Answered: Q1) FIND THE FORECASTING FOR YEAR 2042,…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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-
Identify each of the following as either a parameter or a statistic. The average annual interest rate on 15 credit cards. The percentage of all libraries in a city equipped with VR (virtual reality) technology. The number of results on the first 3 pages of your Google search matching your exact search terms. The average price of ten randomly selected wireless earbuds. SUBMIT QUESTION SAVE PROGRESS 760 (click to select) (click to select) (click to select) (click to select) SUBMIT A
Price SqFt 600000 2767 545000 2731 314900 2051 419000 2084 365000 2270 479000 1950 323000 1235 339900 2116 399000 1644 552000 2415 223017 1375 315777 1529 499000 2223 575000 2327 342000 1879 375000 1558 349000 2012 485000 1200 549888 1410 295000 1943 399000 1827 306999 1840 265200 1636 479000 2357 249700 1152 539500 2650 365000 2154 295900 1279 499000 2156 526000 2493 514900 2390 346000 1347 460000 2120 389000 1917 499000 1200 405000 2643 389900 1789 545000 2327 339000 1742 425000 1746 479000 1421 392000 2569 Can square feet explain prices? Provide evidence to support your answer. If the square feet is 2418, what is the expected price for the home? Please include the excel function.
Please answer the following question using the images provided for data in the images. 1. Which of the following time periods will have the largest annual average increase in the percentage of jobs that could be fully automated (based on the provided images attached)? A) 2020-2028 B) 2028-2030 C) 2030-2035 D) 2035-2040 E) 2040-2050
Stock Market Listed on the top of the next page in order by row are the annual high values of the Dow Jones Industrial Average for each year beginning with 1990. Find the best model and then predict the value for the year 2014 (the last year listed). Is the predicted value close to the actual value of 18,054?
The table shows the leading causes of death in a certain country in a recent year. The population of the country was 311311 million. If you lived in a typical city of 500,000, how many people would you expect to die of cancercancer each year? Cause Deaths Cause Deaths Heart disease 596 comma 700596,700 Alzheimer's disease 84 comma 90084,900 Cancer 575 comma 300575,300 Diabetes 73 comma 40073,400 Chronic respiratory diseases 143 comma 100143,100 Pneumonia/Influenza 53 comma 40053,400 Stroke 128 comma 600128,600 Kidney disease 45 comma 30045,300 Accidents 122 comma 500122,500 Suicide 38 comma 60038,600 About people would be expected to die of cancer each year. (Type a whole number. Round to the nearest person as needed.)
If a forecaster wanted to choose a forecasting model that avoided having a large forecasting error in any given period, which error metric should they use when evaluating their forecasting options? CFE O AFE MAD MAPE O MSE
1) Explain what Type I errors is 2) Provide two real-life examples of a Type I error
Relate cycles, seasonality and trends in time series What is their relevance in such type of forecasting?
Example 20.22 Splice the two indices with base-year 1990 = 100. Year Index 1990 100 1991 110 1992 120 1993 130 1994 150 1995 X₁ 1996 X2 1997 X3 (Base 1994 = 100) 100 120 150 180
apartment x1 x2 1 187 186 2 170 167 3 162 163 4 144 153 5 180 189 6 143 149 7 217 220 8 198 196 9 178 184 10 211 215 11 209 222 12 205 204 13 205 192 14 189 183 15 162 166 16 184 187 17 174 176 18 186 177 19 145 153 20 209 209 21 192 195 22 174 179 23 139 144 24 160 159 25 188 190 26 189 190 27 193 198 28 223 223 29 177 173 30 197 200 31 183 188 32 160 174 33 186 187 34 178 190 35 166 175 36 187 202 37 184 179 38 141 147 39 162 164 40 140 148 41 183 181 42 164 164 43 198 193 44 205 201 45 190 188 46 211 207 47 209 197 48 196 191 49 160 164 50 187 186 51 228 221 52 166 162…
Plot the sales revenue figures and appropriate trend line on a graph and identify from this the choice of model for working out the seasonal component. Using the appropriate seasonal model, complete the calculations that are required to produce the required forecasts for quarters 1, 2, 3 and 4 of 2021. On the basis of your analysis explain the recommendation that you would make to ALAW Ltd regarding its future plans.

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Q1) FIND THE FORECASTING FOR YEAR 2042, 2043, 2044 Years 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 Home value 1000000 1200000 1410000 1640000 1890000 2000000 2200000 2400000 2680000 2800000 3120000 3270000