Probability and Statistics for Engineering and the Sciences
9th Edition
ISBN: 9781305251809
Author: Jay L. Devore
Publisher: Cengage Learning
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Textbook Question
Chapter 7.2, Problem 18E
The U.S. Army commissioned a study to assess how deeply a bullet penetrates ceramic body armor (“Testing Body Armor Materials for Use by the U.S. Army-Phase III,” 2012). In the standard test, a cylindrical clay model is layered under the armor vest. A projectile is then fired, causing an indentation in the clay. The deepest impression in the clay is measured as an indication of survivability of someone wearing the armor. Here is data from one testing organization under particular experimental conditions; measurements (in mm) were made using a manually controlled digital caliper:
- a. Construct a boxplot of the data and comment on interesting features.
- b. Construct a normal probability plot. Is it plausible that impression depth is
normally distributed ? Is a normal distribution assumption needed in order to calculate a confidence interval or bound for the true average depth μ using the foregoing data? Explain. Use the accompanying Minitab output as a basis for calculating and interpreting an upper confidence bound for μ with a confidence level of 99%.
Variable | Count | Mean | SE Mean | StDev |
Depth | 83 | 33.370 | 0.578 | 5.268 |
Q1 | Median | Q3 | IQR |
30.400 | 33.500 | 36.000 | 5.600 |
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A researcher hypothesizes that in a certain country the net annual growth of private sector purchases of government bonds, B, is positively related to the nominal rate of interest on the bonds, NI, and negatively related to the rate of inflation Π:
Bt = a0 + a1NIt + a2Π t + ut
Note that it may be hypothesized that B depends on the real rate of interest on bonds, R, where R = NI – Π.
Using a sample of 56 annual observations, s/he estimates the following equations:
(1) Bt = 0.43 + 0.90NIt - 0.97Πt R21 = 0.962, SSR1 = 2.20, QRESET(F1,52) = 16.6
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(8.84) (36.1)
(4) NIt = 0.08 + 0.94Πt R24 = 0.997, SSR4 = 0.18, QRESET(F1,53) = 1.4…
Chapter 7 Solutions
Probability and Statistics for Engineering and the Sciences
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