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Using the unemployment data​ provided, investigate the association between the male unemployment rate in 2014 and 2017 for a sample of 52 countries. Find a regression model predicting the 2017 rate from the 2014 rate for the sample of 52 countries then complete parts a through c below. A. Construct a plot of the residuals against the 2014 rate. B. Construct a Normal probability plot of the residuals and evaluate the plots to determine if a linear regression is appropriate.  C. Test an appropriate hypothesis to determine if the association is significant. Determine the test statistic. Determine the​ P-value. Make a conclusion. What percentage of the variability in the 2017 rate is accounted for by the regression​ model?

Using the unemployment data​ provided, investigate the association between the male unemployment rate in 2014 and 2017 for a sample of 52 countries. Find a regression model predicting the 2017 rate from the 2014 rate for the sample of 52 countries then complete parts a through c below. A. Construct a plot of the residuals against the 2014 rate. B. Construct a Normal probability plot of the residuals and evaluate the plots to determine if a linear regression is appropriate.  C. Test an appropriate hypothesis to determine if the association is significant. Determine the test statistic. Determine the​ P-value. Make a conclusion. What percentage of the variability in the 2017 rate is accounted for by the regression​ model?

MATLAB: An Introduction with Applications
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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Using the unemployment data​ provided, investigate the association between the male unemployment rate in 2014 and 2017 for a sample of 52 countries. Find a regression model predicting the 2017 rate from the 2014 rate for the sample of 52 countries then complete parts a through c below.

A. Construct a plot of the residuals against the 2014 rate.

B. Construct a Normal probability plot of the residuals and evaluate the plots to determine if a linear regression is appropriate. 

C. Test an appropriate hypothesis to determine if the association is significant. Determine the test statistic. Determine the​ P-value. Make a conclusion. What percentage of the variability in the 2017 rate is accounted for by the regression​ model?

**Table: Country Rate Comparison for 2014 and 2017** | Country | Rate 2014 | Rate 2017 | |---------|-----------|-----------| | 1 | 23.3 | 21.3 | | 2 | 19.9 | 11.8 | | 3 | 11.9 | 11.8 | | 4 | 8.9 | 11.9 | | 5 | 20.1 | 16.9 | | 6 | 26.7 | 23.3 | | 7 | 14.3 | 14.1 | | 8 | 16.6 | 14.7 | | 9 | 13.6 | 11.1 | | 10 | 11.1 | 11.4 | | 11 | 29.8 | 30.7 | | 12 | 8.1 | 14.9 | | 13 | 21.6 | 22.7 | | 14 | 7.3 | 7.8 | | 15 | 15.6 | 12.5 | | 16 | 21.6 | 18.6 | | 17 | 25.7 | 16.6 | | 18 | 22.4 | 24.1 | | 19 | 24.8 | 25.5 | | 20 | 13.1 | 27.5 | | 21 | 18.5 | 18.7 | | 22 | 21.8 | 15.8 | | 23 | 15.6 | 19.6 | | 24 | 19.4 | 8.5 | | 25 | 8.7 | 9.7 | | 26 | 21.4 | 16.8 | | 27 | 11.5 | 9.3 | | 28 |
Transcribed Image Text:**Table: Country Rate Comparison for 2014 and 2017** | Country | Rate 2014 | Rate 2017 | |---------|-----------|-----------| | 1 | 23.3 | 21.3 | | 2 | 19.9 | 11.8 | | 3 | 11.9 | 11.8 | | 4 | 8.9 | 11.9 | | 5 | 20.1 | 16.9 | | 6 | 26.7 | 23.3 | | 7 | 14.3 | 14.1 | | 8 | 16.6 | 14.7 | | 9 | 13.6 | 11.1 | | 10 | 11.1 | 11.4 | | 11 | 29.8 | 30.7 | | 12 | 8.1 | 14.9 | | 13 | 21.6 | 22.7 | | 14 | 7.3 | 7.8 | | 15 | 15.6 | 12.5 | | 16 | 21.6 | 18.6 | | 17 | 25.7 | 16.6 | | 18 | 22.4 | 24.1 | | 19 | 24.8 | 25.5 | | 20 | 13.1 | 27.5 | | 21 | 18.5 | 18.7 | | 22 | 21.8 | 15.8 | | 23 | 15.6 | 19.6 | | 24 | 19.4 | 8.5 | | 25 | 8.7 | 9.7 | | 26 | 21.4 | 16.8 | | 27 | 11.5 | 9.3 | | 28 |
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