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Exercise 35

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Murders and poverty, Part II. Exercise 8.25 presents regression output from a model for predicting annual murders per million from percentage living in poverty based on a random sample of 20 metropolitan areas. The model output is also provided below.

Estimate Std. Error t value Pr(>>∣|t∣|)
(Intercept) -29.901 7.789 -3.839 0.001
poverty% 2.559 0.390 6.562 0.000
s=5.512R2=70.52%Radj2=68.89%s=5.512\qquad R^{2}=70.52\%\qquad R^{2}_{adj}=68.89\%

  1. What are the hypotheses for evaluating whether poverty percentage is a significant predictor of murder rate?

  2. State the conclusion of the hypothesis test from part (a) in context of the data.

  3. Calculate a 95% confidence interval for the slope of poverty percentage, and interpret it in context of the data.

  4. Do your results from the hypothesis test and the confidence interval agree? Explain.

Diez, Barr & Çetinkaya-Rundel, OpenIntro Statistics, Introduction to linear regression, End-of-Chapter Exercises, Exercise 35

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Adapted from OpenIntro Statistics © 2019 David Diez, Mine Çetinkaya-Rundel & Christopher D. Barr. Licensed under CC BY-SA 3.0. Source: OpenIntro Statistics. Imported at revision fee2509.