Applied Statistics in Business and Economics
5th Edition
ISBN: 9781259329050
Author: DOANE
Publisher: MCG
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Question
Chapter 16.7, Problem 14SE
a.
To determine
Check the column sums by converting the data into ranks.
b.
To determine
Find the Spearman’s rank
c.
To determine
Identify whether to reject the hypothesis of
d.
To determine
Check the findings using MegaStat.
e.
To determine
Find the Pearson
Explain why rank correlation might be preferred.
f.
To determine
Explain why rank correlation might be preferred.
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Check out a sample textbook solutionChapter 16 Solutions
Applied Statistics in Business and Economics
Ch. 16.2 - Prob. 1SECh. 16.2 - Prob. 2SECh. 16.2 - Prob. 3SECh. 16.2 - Prob. 4SECh. 16.3 - A sample of 28 student scores on the chemistry...Ch. 16.3 - Prob. 6SECh. 16.4 - Prob. 7SECh. 16.4 - Prob. 8SECh. 16.5 - Prob. 9SECh. 16.5 - The results shown below are mean productivity...
Ch. 16.6 - Consumers are asked to rate the attractiveness of...Ch. 16.6 - Prob. 12SECh. 16.7 - Prob. 13SECh. 16.7 - Prob. 14SECh. 16 - Prob. 1CRCh. 16 - Prob. 2CRCh. 16 - Prob. 3CRCh. 16 - Prob. 4CRCh. 16 - Prob. 5CRCh. 16 - Prob. 6CRCh. 16 - Prob. 7CRCh. 16 - Prob. 8CRCh. 16 - Prob. 9CRCh. 16 - Prob. 10CRCh. 16 - (a) Why is a significant correlation not proof of...Ch. 16 - Prob. 15CECh. 16 - Prob. 16CECh. 16 - Prob. 17CECh. 16 - Prob. 18CECh. 16 - Prob. 19CECh. 16 - Instructions: In all exercises, you may use a...Ch. 16 - Prob. 21CECh. 16 - Prob. 22CECh. 16 - Prob. 23CECh. 16 - Prob. 24CECh. 16 - Prob. 25CECh. 16 - Instructions: In all exercises, you may use a...Ch. 16 - Prob. 27CECh. 16 - Instructions: In all exercises, you may use a...Ch. 16 - Prob. 29CECh. 16 - Prob. 30CECh. 16 - Prob. 31CECh. 16 - Prob. 32CECh. 16 - Prob. 33CECh. 16 - Prob. 34CECh. 16 - Instructions: In all exercises, you may use a...Ch. 16 - Prob. 36CECh. 16 - Prob. 37CE
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- For the following exercises, use Table 4 which shows the percent of unemployed persons 25 years or older who are college graduates in a particular city, by year. Based on the set of data given in Table 5, calculate the regression line using a calculator or other technology tool, and determine the correlation coefficient. Round to three decimal places of accuracyarrow_forwardNoise and Intelligibility Audiologists study the intelligibility of spoken sentences under different noise levels. Intelligibility, the MRT score, is measured as the percent of a spoken sentence that the listener can decipher at a cesl4ain noise level in decibels (dB). The table shows the results of one such test. (a) Make a scatter plot of the data. (b) Find and graph the regression line. (c) Find the correlation coefficient. Is a linear model appropriate? (d) Use the linear model in put (b) to estimate the intelligibility of a sentence at a 94-dB noise level.arrow_forwardOlympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s pole vault height has fallen below the value predicted by the regression line in Example 2. This might have occurred because when the pole vault was a new event there was much room for improvement in vaulters’ performances, whereas now even the best training can produce only incremental advances. Let’s see whether concentrating on more recent results gives a better predictor of future records. (a) Use the data in Table 2 (page 176) to complete the table of winning pole vault heights shown in the margin. (Note that we are using x=0 to correspond to the year 1972, where this restricted data set begins.) (b) Find the regression line for the data in part ‚(a). (c) Plot the data and the regression line on the same axes. Does the regression line seem to provide a good model for the data? (d) What does the regression line predict as the winning pole vault height for the 2012 Olympics? Compare this predicted value to the actual 2012 winning height of 5.97 m, as described on page 177. Has this new regression line provided a better prediction than the line in Example 2?arrow_forward
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