Probability and Statistics

The Mendelian theory states that the number of a type of peas that fall into the classifications round and yellow, wrinkled and yellow, round and green, and wrinkled and green should be in the ratio 9:3:3:1. Suppose that 100 such peas revealed 56, 19, 17, and 8 in the respective categories. Are these data consistent with the model? Use α = .05. (The expression 9:3:3:1 means that 9/16 of the peas should be round and yellow, 3/16 should be wrinkled and yellow, etc.)

The Mendelian theory states that the number of a type of peas that fall into the classifications round and yellow, wrinkled and yellow, round and green, and wrinkled and green should be in the ratio 9:3:3:1. Suppose that 100 such peas revealed 56, 19, 17, and 8 in the respective categories. Are these data consistent …

The Mendelian theory states that the number of a type of peas that fall into the classifications round and yellow, wrinkled and yellow, round and green, and wrinkled and green should be in the ratio 9:3:3:1. Suppose that 100 such peas revealed 56, 19, 17, and 8 in the respective categories. Are these data consistent with the model? Use α = .05. (The expression 9:3:3:1 means that 9/16 of the peas should be round and yellow, 3/16 should be wrinkled and yellow, etc.) Read More »

Your portfolio is invested 30 percent each in A and C, and 40 percent in B. What is the expected return of the portfolio? (Do not round intermediate calculations. Enter your answer as a percent rounded to 2 decimal places, e.g., 32.16.) What is the variance of this portfolio? (Do not round intermediate calculations and round your answer to 5 decimal places, e.g., 32.16161.) What is the standard deviation? (Do not round intermediate calculations. Enter your answer as a percent rounded to 2 decimal places, e.g., 32.16.

EXPERT ANSWER Investment in Stock A =0.30 Investment in Stock A =0.40 Investment in Stock C=0.30 Boom E(Rp)= 0.30(0.34) +0.40( 0.44) +0.30(0.35) = 0.102+ 0.176+ 0.105 =0.3830 or 38.30% Good E(Rp)= 0.30(0.18) +0.40( 0.15) +0.30(0.09) = 0.054+ 0.06+ 0.027 = 0.1410 or 14.10% Poor E(Rp)= 0.30(-0.02) +0.40( -0.05) +0.30(-0.04) = -0.006+ -0.02+ -0.01 = -0.0380 …

Your portfolio is invested 30 percent each in A and C, and 40 percent in B. What is the expected return of the portfolio? (Do not round intermediate calculations. Enter your answer as a percent rounded to 2 decimal places, e.g., 32.16.) What is the variance of this portfolio? (Do not round intermediate calculations and round your answer to 5 decimal places, e.g., 32.16161.) What is the standard deviation? (Do not round intermediate calculations. Enter your answer as a percent rounded to 2 decimal places, e.g., 32.16. Read More »

A confidence interval estimate is desired for the gain in a circuit on a semiconductor device. Assume that gain is normally distributed with standard deviation s = 25. (a) How large must n be if the length of the 95% CI is to be not greater than 50? (b) How large must n be if the length of the 99% CI is to be not greater than 50?

A confidence interval estimate is desired for the gain in a circuit on a semiconductor device. Assume that gain is normally distributed with standard deviation s = 25. (a) How large must n be if the length of the 95% CI is to be not greater than 50? (b) How large must n be if …

A confidence interval estimate is desired for the gain in a circuit on a semiconductor device. Assume that gain is normally distributed with standard deviation s = 25. (a) How large must n be if the length of the 95% CI is to be not greater than 50? (b) How large must n be if the length of the 99% CI is to be not greater than 50? Read More »

A confidence interval estimate is desired for the gain in a circuit on a semiconductor device. Assume that gain is normally distributed with standard deviation s = 15.

A confidence interval estimate is desired for the gain in a circuit on a semiconductor device. Assume that gain is normally distributed with standard deviation s = 15. (a) How large must n be if the length of the 95% CI is to be not greater than 30? (b) How large must n be if …

A confidence interval estimate is desired for the gain in a circuit on a semiconductor device. Assume that gain is normally distributed with standard deviation s = 15. Read More »

An article in Medicine and Science in Sports and Exercise [“Maximal Leg-Strength Training Improves Cycling Economy in Previously Untrained Men” (2005, Vol. 37, pp. 131-136)] studied cycling performance before and after eight weeks of leg-strength training. Seven previously untrained males performed leg-strength training three days per week for eight weeks (with four sets of five replications at 85% of one repetition maximum). Peak power during incremental cycling increased to a mean of 315 watts with a standard deviation of 16 watts. Construct a 95% confidence interval for the mean peak power after training.

EXPERT ANSWER

A manufacturer is interested in the output voltage of a power supply used in a PC. Output voltage is assumed to be normally distributed with a standard deviation 0.25 volts and the manufacturer wishes to test the hypothesis H0: µ = 5 against H1: µ > 5 volts using n = 8 units.

A manufacturer is interested in the output voltage of a power supply used in a PC. Output voltage is assumed to be normally distributed with a standard deviation 0.25 volts and the manufacturer wishes to test the hypothesis H0: µ = 5 against H1: µ > 5 volts using n = 8 units. (a) The …

A manufacturer is interested in the output voltage of a power supply used in a PC. Output voltage is assumed to be normally distributed with a standard deviation 0.25 volts and the manufacturer wishes to test the hypothesis H0: µ = 5 against H1: µ > 5 volts using n = 8 units. Read More »

A manufacturer produces crankshafts for an automobile engine. The crankshafts wear after 100,000 miles (0.0001 inch) is of interest because it is likely to have an impact on warranty claims. A random sample of n = 15 shafts is tested and ẋ = 2.78. It is known that σ = 0.9 and that wear is normally distributed.

A manufacturer produces crankshafts for an automobile engine. The crankshafts wear after 100,000 miles (0.0001 inch) is of interest because it is likely to have an impact on warranty claims. A random sample of n = 15 shafts is tested and ẋ = 2.78. It is known that σ = 0.9 and that wear is normally distributed. Test H0 : μ ≠3 using α = 0.05. …

A manufacturer produces crankshafts for an automobile engine. The crankshafts wear after 100,000 miles (0.0001 inch) is of interest because it is likely to have an impact on warranty claims. A random sample of n = 15 shafts is tested and ẋ = 2.78. It is known that σ = 0.9 and that wear is normally distributed. Read More »

A manufacturer produces crankshafts for an automobile engine. The crankshafts wear after 100,000 miles (0.0001 inch) is of interest because it is likely to have an impact on warranty claims. A random sample of n = 15 shafts is tested and x = 2.78. It is known that σ = 0.9 and that wear is normally distributed.

A manufacturer produces crankshafts for an automobile engine. The crankshafts wear after 100,000 miles (0.0001 inch) is of interest because it is likely to have an impact on warranty claims. A random sample of n = 15 shafts is tested and x = 2.78. It is known that σ = 0.9 and that wear is …

A manufacturer produces crankshafts for an automobile engine. The crankshafts wear after 100,000 miles (0.0001 inch) is of interest because it is likely to have an impact on warranty claims. A random sample of n = 15 shafts is tested and x = 2.78. It is known that σ = 0.9 and that wear is normally distributed. Read More »