William used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). His estimated regression equation was Crime = 428 + 0.050 Income. We can conclude that Group of answer choices the intercept is irrelevant since zero median income is impossible in a large city. the slope is small so Income has no effect on Crime. wealthy individuals tend to commit more crimes, on average. crime seems to create additional income in a city.
William used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). His estimated regression equation was Crime = 428 + 0.050 Income. We can conclude that Group of answer choices the intercept is irrelevant since zero median income is impossible in a large city. the slope is small so Income has no effect on Crime. wealthy individuals tend to commit more crimes, on average. crime seems to create additional income in a city.
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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William used a sample of 68 large U.S. cities to estimate the relationship between Crime (annual property crimes per 100,000 persons) and Income (median annual income per capita, in dollars). His estimated regression equation was Crime = 428 + 0.050 Income. We can conclude that
Group of answer choices
the intercept is irrelevant since zero median income is impossible in a large city.
the slope is small so Income has no effect on Crime.
wealthy individuals tend to commit more crimes, on average.
crime seems to create additional income in a city.
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