Two suppliers manufacture a plastic gear used in a laser printer. The impact strength of these gears measured in foot-pounds is an important characteristic. A random sample of 10 gears from supplier 1 results in ₁ = 290 and s₁ = 12, and another random sample of 16 gears from the second supplier results in x₂ = 321 and s₂ = 22. Construct a 95% confidence interval estimate for the difference in mean impact strength and explain how this interval could be used to answer the question posed regarding supplier-to- supplier differences. Assume that both populations are normally distributed but the variances are not equal (Case 2: o² #02) a. 17.175 <= u1-u2 <= 44.825. Because zero is contained in the confidence interval, we conclude that supplier 2 provides gears with a higher mean impact strength than supplier 1 with 90% confidence O b. None among the choices O c. 17.175 <= u1-u2 <= 44.825. Because zero is not contained in the confidence interval, we conclude that supplier 2 provides gears with a higher mean impact strength than supplier 1 with 95% confidence O d. 17.175 <= u1-u2 <= 44.825. Because zero is not contained in the confidence interval, we conclude that supplier 2 provides gears with a lower mean impact strength than supplier 1 with 99% confidence
Two suppliers manufacture a plastic gear used in a laser printer. The impact strength of these gears measured in foot-pounds is an important characteristic. A random sample of 10 gears from supplier 1 results in ₁ = 290 and s₁ = 12, and another random sample of 16 gears from the second supplier results in x₂ = 321 and s₂ = 22. Construct a 95% confidence interval estimate for the difference in mean impact strength and explain how this interval could be used to answer the question posed regarding supplier-to- supplier differences. Assume that both populations are normally distributed but the variances are not equal (Case 2: o² #02) a. 17.175 <= u1-u2 <= 44.825. Because zero is contained in the confidence interval, we conclude that supplier 2 provides gears with a higher mean impact strength than supplier 1 with 90% confidence O b. None among the choices O c. 17.175 <= u1-u2 <= 44.825. Because zero is not contained in the confidence interval, we conclude that supplier 2 provides gears with a higher mean impact strength than supplier 1 with 95% confidence O d. 17.175 <= u1-u2 <= 44.825. Because zero is not contained in the confidence interval, we conclude that supplier 2 provides gears with a lower mean impact strength than supplier 1 with 99% confidence
A First Course in Probability (10th Edition)
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Author:Sheldon Ross
Publisher:Sheldon Ross
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Transcribed Image Text:Two suppliers manufacture a plastic gear used in a laser printer. The impact strength of these
gears measured in foot-pounds is an important characteristic. A random sample of 10 gears from
supplier 1 results in ₁ = 290 and s₁ = 12, and another random sample of 16 gears from the
second supplier results in x₂ = 321 and s₂ = 22.
Construct a 95% confidence interval estimate for the difference in mean impact strength and
explain how this interval could be used to answer the question posed regarding supplier-to-
supplier differences. Assume that both populations are normally distributed but the variances are
not equal (Case 2: o² #02)
a. 17.175 <= u1-u2 <= 44.825. Because zero is contained in the confidence interval, we conclude that supplier 2
provides gears with a higher mean impact strength than supplier 1 with 90% confidence
O b. None among the choices
O c. 17.175 <= u1-u2 <= 44.825. Because zero is not contained in the confidence interval, we conclude that
supplier 2 provides gears with a higher mean impact strength than supplier 1 with 95% confidence
O d. 17.175 <= u1-u2 <= 44.825. Because zero is not contained in the confidence interval, we conclude that
supplier 2 provides gears with a lower mean impact strength than supplier 1 with 99% confidence
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