The following time series represents the number of automobiles sold by a car dealership each of the past five months.t 12 3 4 5Time Series ValueYt7 12 10 13 16(a) Construct a time series plot.16942914+121084001234Time Period (t)5 6What type of pattern exists in the data?O The time series plot shows a seasonal pattern.O The time series plot shows a linear trend.O The time series plot shows a nonlinear trend.O The time series plot shows a horizontal pattern.(c) What is the forecast for t = 6?DOTime Series Value16ܗ ܠ ܚ ܘ ܗ141220123 4Time Period (t)5(b) Use simple linear regression analysis to find the parameters for the line that minimizes MSE for this time series.6GOTime Series Value1614001234Time Period (t)56Time Series Value1642086001234Time Period (t)56a

Answered: The following time series represents…

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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Year Percent of workers paid hourly rates 1979 61.2 1980 60.7 1981 61.3 1982 61.3 1983 61.8 1984 61.7 1985 61.8 1986 62.0 1987 62.7 1990 62.8 1992 62.9 The percent of female wage and salary workers who are paid hourly rates is given above for the years 1979-1992. a. Using "year" as the independent variable and "percent" as the dependent variable, make a scatter plot of the data. b. Does it appear from inspection that there is a relationship between the variables? c. Find the estimated percents for 1991 and 1988. d. Use the two points in part C to plot the least squares line on your graph from part A.
Life Expectancies Is there a relationship between the life expectancy for men and the life expectancy for women in a given country? A random sample of nonindustrialized countries was selected, and the life expectancy in years is listed for both men and women. Are the variables linearly related? Men 60.2, 43.9, 59.8, 66.1, 68.4, 64.8 Women 60.0, 43.8, 56.6, 72.7, 63.5, 66 Draw the scatter plot for the variables. Compute the value of the correlation coefficient r= state the hypothesis h0: h1: critical value(s) reject or accept the null hypothesis Give a brief explanation of the type of relationship
The data in the table represents the amount of fish in a pond after a set amount of weeks. Week 0 1 2 3 4 5 Fish 12 17 24 30 35 42 If the data continues the same linear trend, how many fish do you expect to be in the pond on week 7? 48 fish 40 fish 60 fish 54 fish
Below are given the annual production figures (in thousand tonnes) of a fertiliser factory : Year 2011 2012 2013 2014 2015 2016 2017 Production : 70 75 90 91 95 98 100 (1) Fit a straight line trend by the method of least squares and tabulate the trend values. (i) Convert your annual trend equation into a monthly trend equation.
Q27
create a Scatter plot using the attached information and explain why using this type of graph is important in business
Help with 4
The following table present quarterly sales for a company over the three years (a) Fit the trend as a linear function of time t and predict the sales for the 4th year? Year 2 Year 3 309 405 326 429 369 446 416 465 quarter 1 2 3 4 Year 1 241 263 273 292
Q. 16. step by stepsolutiomn please Scatter plots and Equations of Lines, Writing an Equation for a trend line Which graph shows the best trend line for the following data Practice (weeks) 6 8 10 12 14 16 18 Score 15.5 21.5 26.5 34 33 37 41
The following time series shows the sales of supermarket chain over the last six months. Month Sales ($ 000) August 2021 250 Sep 2021 280 Oct 2021 295 Nov 2021 320 Dec 2021 380 Jan 2022 360 Develop a linear trend equation that can be used to forecast sales in Feb 2022. Forecast the sales in Feb 2021 using a three-period weighted moving average designed with the following weights: Nov 2021 weight 0.6, Dec 2021 weight 0.3 and Jan 2022 weight 0.1. Which method (A or B) is the best? Explain why.
a. Obtain the linear trend equation for the following data on new checking accounts at Fair Savings Bank and use it to predict expected new checking accounts for periods 16 through 19. (Round your intermediate calculations and final answers to 2 deci places.) Period New Accounts Period, New Accounts Period New Accounts 1 2 3 4 Y Y16 Y17 Y18 Y19 200 214 211 220 235 6 7 8 9 10 237 248 250 258 267 11 12 13 14 15 281 275 287 288 316
Find text or tools Use the information provided below to answer questions 24-25. INFORMATION The times series graph below shows information about the quarterly number of tourists from the European Union (EU) to vh Africa over the 2021-2023 period. The underlying trend line indicated by the dotted line is defined by the equation, y 703x-176 577. Time ones graph of quarterly number of tourists for EU to South 40000 REANDDIC 300000 2240 2010 200000 150000 18390 1000 0 2 --T Arica (2021-2023) 12920 30000 2013 8 10 1999 18 QUESTION 24 (4 marks) Using data from the graph, estimate the mean seasonal variation (or average seasonal effect) for quarter 4 (Q4) and use it to predict the number of tourists from the EU expected to visit South Africa in quarter 4 of 2024. A. The mean seasonal variation is -25 000; the number of tourists from the EU expected to visit South Africa in quarter 4 of 2024 is 322 825. B. The mean seasonal variation is 25 000, the number of tourists from the EU expected to…

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