34. The following data relate to the number of passenger cars (in million) soldfrom 2007 to 2014 :YearNumberYearNumber5.67.920076.720115.320122008200920104.320135.86.120146.1(a) Fit a straight line trend to the data through 2012 only.(b) Use your result in (a) to estimate production in 2017 and compare with the actual production..

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Answered: 34. The following data relate to the…

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 president of State University wants to forecast student enrollments for this Year academic year based on the following historical data: 5 years ago 4 years ago 3 years ago 2 years ago Last year Enrollments 15.000 16.000 18.000 20.000 21.000 a- What is the forecast for this year using a 3-year weighted moving average where the weights are halved in a descending order from newest to oldest ? b. What is the forecast for this year using the trend line for these data? c. using the MAD find which forecasting technique may be appropriate for this quetion
John Kittle, an independent insurance agent, uses a five-year moving average to forecast the number of claims made in a single year for one of the large insurance companies he sells for. He has just discovered that a clerk in his employ incorrectly entered the number of claims made four years ago as 1,400 when it should have been 1,200.a. What adjustment should Mr. Kittle make in next year’s forecast to take into account the corrected value of the number of claims four years ago?b. Suppose that Mr. Kittle used simple exponential smoothing with a = .2instead of moving averages to determine his forecast. What adjustment is now required in next year’s forecast? (Note that you do not need to know the value of the forecast for next year in order to solve this problem.)
Create a 2-D line chart of Cash Sales for months 1-18. Add a trend line with a forward forecast of 3 periods to the chart. Be sure to include the R-squared value on the chart. Using =TREND(), complete the forecast table for months 19-21 1 $ 2,145,600 19 2 $ 2,175,200 20 3 $ 2,255,200 21 4 $ 2,505,600 5 $ 2,748,800 6 $ 2,358,000 7 $ 3,165,200 8 $ 3,253,600 9 $ 3,484,000 10 $ 3,731,200 11 $ 3,741,200 12 $ 3,558,800 13 $ 3,771,200 14 $ 3,787,600 15 $ 3,813,600 16 $ 3,822,800 17 $ 3,828,000 18 $ 3,897,200
Are the data displayed in the graph above discrete or continuous? What is the level of measurement of the data? Are the data above time series or cross-sectional data? Examine the data for each race/ethnicity group. Do the data represent a stationary or nonstationary process? Do any of the race/ethnicity groups exhibit a decreasing trend? Do any of the race/ethnicity groups show a strictly increasing trend over the entire time period from 2000 to 2016?
A scatterplot with no linear trend will have an r value of zero true or false?
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The Credit Risk Department of a major bank estimates the default rate on loans under $10,000 to be 4%. The bank will make 2400 loans that are under $10,000 next month. Find the mean of ^p, where ^p is the proportion of defaults on the 2400 loans under $10,000 to be made next month.
Suppose the following table shows the approximate price of a certain stock in December of each year from 2005 through 2014, as well as the 4-year moving averages for 2005 through 2007.† Complete the table by computing the remaining 4-year moving averages. (Note the peak in 2007 and the drop in subsequent years.) Round each average to the nearest dollar. (Chart in picture)
Amex PLC has gathered following information on the sales of face mask from April 2020 toSeptember 2020.Month Sales ($)April 17,000May 18,000June 19,500July 22,000August 21,000September 23,000You are required to;a. Using linear trend equation forecast the sales of face masks for October 2020.
The following is the production data for fried indomie (million pcs) in 2011 - 2020 consecutively as follows: 3, 8, 14, 13, 15, 16, 12, 17, 18, 17. Determine the value of the production trend using Moving Average Method!
Suppose the following table shows the approximate price of a certain stock in December of each year from 2005 through 2014, as well as the 4-year moving averages for 2005 through 2007.† Complete the table by computing the remaining 4-year moving averages. (Note the peak in 2007 and the drop in subsequent years.) Round each average to the nearest dollar.

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