STATISTICS F/BUSINESS+ECONOMICS-TEXT
STATISTICS F/BUSINESS+ECONOMICS-TEXT
13th Edition
ISBN: 9781305881884
Author: Anderson
Publisher: CENGAGE L
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Chapter 20.2, Problem 1E

The following table reports prices and usage quantities for two items in 2009 and 2011.

Chapter 20.2, Problem 1E, The following table reports prices and usage quantities for two items in 2009 and 2011. a. Compute

  1. a. Compute price relatives for each item in 2011 using 2009 as the base period.
  2. b. Compute an unweighted aggregate price index for the two items in 2011 using 2009 as the base period.
  3. c. Compute a weighted aggregate price index for the two items using the Laspeyres method.
  4. d. Compute a weighted aggregate price index for the two items using the Paasche method.
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Construct the following Weighted Aggregative Price index for 2021 on the basis of 2017 data; Laspeyer’s Index Paasche’s Index Fisher’s Ideal Index Dorbish and Bowley’s Index Commodity Prices Quantities   2017 2021 2017 2021 A 150 330 8000 11000 B 55 105 700 650 C 4420 9000 30 35 D 700 1334 475 365 E 320 320 436 780
The following table presents prices, in thousands of dollars, of single-family homes for 20  of the largest metropolitan areas in the United States for the first quarter of  2012 and the first quarter of 2013. .   Metro Area   2012   2013 Boston, MA   311.5   332.2 Chicago, IL   157.2   159.4 Cincinnati, OH   112.5   121.0 Cleveland, OH   84.9   101.0 Dallas, TX   148.2   160.4 Denver, CO   226.4   261.2 Houston, TX   152.1   163.7 Los Angeles, CA   122.1   155.1 Miami, FL   182.0   219.9 Minneapolis, MN   147.3   170.6   Metro Area   2012   2013 New York, NY   363.8   368.2 Philadelphia, PA   193.5   197.7 Phoenix, AZ   129.9   169.0 Portland, OR   208.6   246.5 Riverside, CA   174.3   216.7 St. Louis, MO   103.7   111.0 San Diego, CA   359.5   412.3 San Francisco, CA   448.0…
Dave Fletcher, the general manager of North Carolina Engineering Corporation (NCEC), thinks that his firm’s engineer-ing services contracted to highway construction firms are directly related to the volume of highway construction business contractedwith companies in his geographic area. He wonders if this is reallyso, and if it is, can this information help him plan his operationsbetter by forecasting the quantity of his engineering servicesrequired by construction firms in each quarter of the year? Thefollowing table presents the sales of his services and total amountsof contracts for highway construction over the past eight quarters:   a) Using this data, develop a regression equation for predictingthe level of demand of NCEC’s services. b) Determine the coefficient of correlation and the standard errorof the estimate.
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