Student Solutions Manual for Basic Business Statistics
13th Edition
ISBN: 9780321926708
Author: David M. Levine; Mark L. Berenson; Timothy C. Krehbiel; Kathryn A. Szabat; David F. Stephan
Publisher: Pearson Education
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Chapter 16, Problem 7PS
a.
To determine
Plot the time series.
b.
To determine
Fit a three-year Moving Average to the data and plot results.
c.
To determine
Find the exponentially smoothed series using a smoothing coefficient of
d.
To determine
Determine the exponentially smoothed forecast for the year 2012.
e.
To determine
Find the exponentially smoothed series using a smoothing coefficient of
To determine
Determine the exponentially smoothed forecast for the year 2012 if
f.
To determine
Compare the results obtained in parts (d) and (e).
g.
To determine
Write a conclusion on the retail price of coffee in Portugal.
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1) The following data are US exports to Mexico. Complete the missing values.
a) Fill in the table.
b) Note that the Adjusted Seasonal Index for March is 112.7. What does this number mean?
To estimate the Trend, a regression of the Seasonally Adjusted Series on a trend yielded the following results.
c) What is your forecast of US Exports to Mexico for March 2005 (which would be the 50th observation)?
11) The following data are US exports to Mexico. Complete the missing values.
YOU WILL NEED TO USE THE REGRESSION RESULTS BELOW TO HELP COMPLETE THE TABLE ABOVE.
a) Fill in the table.
b) Note that the Adjusted Seasonal Index for March is 112.7. What does this number mean?
To estimate the Trend, a regression of the Seasonally Adjusted Series on a trend yielded the following results.
c) What is your forecast of US Exports to Mexico for March 2005 (which would be the 50th observation)?
c. Predict sales in 15 years.
Chapter 16 Solutions
Student Solutions Manual for Basic Business Statistics
Ch. 16 - If you are using exponential smoothing for...Ch. 16 - Consider a nine-year moving average used to smooth...Ch. 16 - Prob. 3PSCh. 16 - Prob. 4PSCh. 16 - Prob. 5PSCh. 16 - How have stocks performed in the past? The...Ch. 16 - Prob. 7PSCh. 16 - Prob. 8PSCh. 16 - Prob. 9PSCh. 16 - Prob. 10PS
Ch. 16 - The linear trend forecasting equation for an...Ch. 16 - Prob. 12PSCh. 16 - Prob. 13PSCh. 16 - Prob. 14PSCh. 16 - The file ComputerSales contains the U.S. total...Ch. 16 - Prob. 16PSCh. 16 - The file CarProduction contains the number of...Ch. 16 - The average salary of Major League Baseball player...Ch. 16 - Prob. 19PSCh. 16 - Prob. 20PSCh. 16 - Prob. 21PSCh. 16 - Prob. 22PSCh. 16 - You are given an annual time series with 40...Ch. 16 - Prob. 24PSCh. 16 - Prob. 25PSCh. 16 - Prob. 26PSCh. 16 - Using the data for Problem 16.15 on page 646 that...Ch. 16 - Prob. 28PSCh. 16 - Prob. 29PSCh. 16 - Using the average baseball salary from 2000...Ch. 16 - Prob. 31PSCh. 16 - The following residuals are from a linear trend...Ch. 16 - Prob. 33PSCh. 16 - Prob. 34PSCh. 16 - Prob. 35PSCh. 16 - Prob. 36PSCh. 16 - Prob. 37PSCh. 16 - Using the average baseball salary from 2000...Ch. 16 - Prob. 39PSCh. 16 - Prob. 40PSCh. 16 - In forecasting daily time-series data, how many...Ch. 16 - Prob. 42PSCh. 16 - Prob. 43PSCh. 16 - The data in Toys R Us are quarterly revenues...Ch. 16 - Prob. 45PSCh. 16 - Prob. 46PSCh. 16 - Prob. 47PSCh. 16 - The file Silver-Q contains the price in London for...Ch. 16 - Prob. 49PSCh. 16 - What is a time series?Ch. 16 - What are the different components of a time-series...Ch. 16 - What is the difference between moving average and...Ch. 16 - Prob. 53PSCh. 16 - How does the least-squares linear trend...Ch. 16 - How does autoregressive modelling differ from the...Ch. 16 - What are the different approaches to choosing an...Ch. 16 - What is the major difference between using SYX and...Ch. 16 - How does forecasting for monthly or quarterly data...Ch. 16 - Prob. 60PSCh. 16 - Prob. 61PSCh. 16 - The data in the following table, stored in...Ch. 16 - Teachers' Retirement System of the City of New...Ch. 16 - Prob. 64PS
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- For the Texas Shipping Company, the monthly percentages of all shipments received on time over the past 12 months are 82, 86, 87, 89, 84, 85, 84, 86, 75, 95, 90, and 92. a. Construct a time series plot (you can include it in the work file question at the end, not here). Identify what type of pattern, if any, exists in the data? Compare the three-month moving average forecast with an exponential smoothing forecast for alpha= 0.25 and answer the following: b. MSE for 3-month moving average method c. MSE for exponential-smoothing method : d. Which method should be preferred? Answer "3-month MA" or "Exponential Smoothing": e. What is the forecast for next month using the preferred method?arrow_forwardJohn 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.)arrow_forwardThe following data report total, monthly U.S. gasoline sales in millions of dollars from January 2017 to December 2018. (To find the data, go to the site https://www.census.gov/retail/index.html#mrts, find “Monthly Retail Trade Report,” then select “Time Series/Trend Charts.”) d. Evaluate a seasonally adjusted trend forecasting model. What is the MAD? (Round your answers to 3 decimal places.)arrow_forward
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