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times. Typically, what the federal government finds is that "poor" states tend to stay poor and "wealthy" states tend to stay wealthy. Tor the same state at different Would we have gotten information about the 1999 per capita income for a state (denoted by y) from its 1980 per capita income (denoted by x)? The following bivariate data give the per capita income (in thousands of dollars) for a sample of fourteen states in the years 1980 and 1999 (source: U.S. Bureau of Economic Analysis, Survey of Current Business, May 2000). The data are plotted in the scatter plot in Figure 1. 1980 per capita 1999 per capita income, x income, y (in $1000s) (in $1000s) 38 New York Alabama 11.1 33.9 36 7.9 22.9 Kansas 10.0 26.6 Washington Texas Florida North Dakota Colorado Louisiana Maryland 10.9 30.3 10.0 26.5 10.0 28.0 8.1 23.5 10.8 31.7 8.8 22.8 11.2 32.2 Rhode Island South Carolina Johio 9.7 29.7 7.8 23.5 1980 per capita income 10.1 27.1 Explanation Check 1999 per capita income In $1000s)

times. Typically, what the federal government finds is that "poor" states tend to stay poor and "wealthy" states tend to stay wealthy. Tor the same state at different Would we have gotten information about the 1999 per capita income for a state (denoted by y) from its 1980 per capita income (denoted by x)? The following bivariate data give the per capita income (in thousands of dollars) for a sample of fourteen states in the years 1980 and 1999 (source: U.S. Bureau of Economic Analysis, Survey of Current Business, May 2000). The data are plotted in the scatter plot in Figure 1. 1980 per capita 1999 per capita income, x income, y (in $1000s) (in $1000s) 38 New York Alabama 11.1 33.9 36 7.9 22.9 Kansas 10.0 26.6 Washington Texas Florida North Dakota Colorado Louisiana Maryland 10.9 30.3 10.0 26.5 10.0 28.0 8.1 23.5 10.8 31.7 8.8 22.8 11.2 32.2 Rhode Island South Carolina Johio 9.7 29.7 7.8 23.5 1980 per capita income 10.1 27.1 Explanation Check 1999 per capita income In $1000s)

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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The value of the sample correlation coefficient r for these data is approximately 0.917. Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as specified below. (If necessary, consult list of formulas.) (a) What is the value of the slope of the least-squares regression line for these data? Round your answer to at least two decimal places. (b) What is the value of the y-intercept of the least-squares regression line for these data? Round your answer to at least two decimal places.
Transcribed Image Text:The value of the sample correlation coefficient r for these data is approximately 0.917. Answer the following. Carry your intermediate computations to at least four decimal places, and round your answers as specified below. (If necessary, consult list of formulas.) (a) What is the value of the slope of the least-squares regression line for these data? Round your answer to at least two decimal places. (b) What is the value of the y-intercept of the least-squares regression line for these data? Round your answer to at least two decimal places.
In ongoing economic analyses, the federal government compares per capita incomes not only among different states but also for the same state at different times. Typically, what the federal government finds is that "poor" states tend to stay poor and "wealthy" states tend to stay wealthy. Would we have gotten information about the 1999 per capita income for a state (denoted by y) from its 1980 per capita income (denoted by x)? The following bivariate data give the per capita income (in thousands of dollars) for a sample of fourteen states in the years 1980 and 1999 (source: U.S. Bureau of Economic Analysis, Survey of Current Business, May 2000). The data are plotted in the scatter plot in Figure 1. 1980 per capita 1999 per capita income, x income, y (in $1000s) (in $1000s) 38 New York 11.1 33.9 36-- Alabama 7.9 22.9 34- Kansas 10.0 26.6 32+ Washington 10.9 30.3 30- Техas 10.0 26.5 28 Florida 10.0 28.0 26- North Dakota 8.1 23.5 24- Colorado 10.8 31.7 22. Louisiana 8.8 22.8 20 Maryland Rhode Island South Carolina 11.2 32.2 9.7 29.7 7.8 23.5 Ohio 10.1 1980 per capita income 27.1 Explanation Check 1999 per capi ta income (in $1000s)
Transcribed Image Text:In ongoing economic analyses, the federal government compares per capita incomes not only among different states but also for the same state at different times. Typically, what the federal government finds is that "poor" states tend to stay poor and "wealthy" states tend to stay wealthy. Would we have gotten information about the 1999 per capita income for a state (denoted by y) from its 1980 per capita income (denoted by x)? The following bivariate data give the per capita income (in thousands of dollars) for a sample of fourteen states in the years 1980 and 1999 (source: U.S. Bureau of Economic Analysis, Survey of Current Business, May 2000). The data are plotted in the scatter plot in Figure 1. 1980 per capita 1999 per capita income, x income, y (in $1000s) (in $1000s) 38 New York 11.1 33.9 36-- Alabama 7.9 22.9 34- Kansas 10.0 26.6 32+ Washington 10.9 30.3 30- Техas 10.0 26.5 28 Florida 10.0 28.0 26- North Dakota 8.1 23.5 24- Colorado 10.8 31.7 22. Louisiana 8.8 22.8 20 Maryland Rhode Island South Carolina 11.2 32.2 9.7 29.7 7.8 23.5 Ohio 10.1 1980 per capita income 27.1 Explanation Check 1999 per capi ta income (in $1000s)
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