Bundle: Statistics for Business & Economics, Loose-Leaf Version, 13th + MindTap Business Statistics with XLSTAT, 1 term (6 months) Printed Access Card
Bundle: Statistics for Business & Economics, Loose-Leaf Version, 13th + MindTap Business Statistics with XLSTAT, 1 term (6 months) Printed Access Card
13th Edition
ISBN: 9781337148092
Author: David R. Anderson, Dennis J. Sweeney, Thomas A. Williams, Jeffrey D. Camm, James J. Cochran
Publisher: Cengage Learning
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Chapter 16.6, Problem 27E

The following data show the daily closing prices (in dollars per share) for a stock.

Date Price ($)
Nov. 3 82.87
Nov. 4 83.00
Nov. 7 83.61
Nov. 8 83.15
Nov. 9 82.84
Nov. 10 83.99
Nov. 11 84.55
Nov. 14 84.36
Nov. 15 85.53
Nov. 16 86.54
Nov. 17 86.89
Nov. 18 87.77
Nov. 21 87.29
Nov. 22 87.99
Nov. 23 88.80
Nov. 25 88.80
Nov. 28 89.11
Nov. 29 89.10
Nov. 30 88.90
Dec. 1 89.21
  1. a. Define the independent variable Period, where Period = 1 corresponds to the data for November 3, Period = 2 corresponds to the data for November 4, and so on. Develop the estimated regression equation that can be used to predict the closing price given the value of Period.
  2. b. At the .05 level of significance, test for any positive autocorrelation in the data.
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