In: Math
The home run percentage is the number of home runs per 100 times at bat. A random sample of 43 professional baseball players gave the following data for home run percentages.
1.6 | 2.4 | 1.2 | 6.6 | 2.3 | 0.0 | 1.8 | 2.5 | 6.5 | 1.8 |
2.7 | 2.0 | 1.9 | 1.3 | 2.7 | 1.7 | 1.3 | 2.1 | 2.8 | 1.4 |
3.8 | 2.1 | 3.4 | 1.3 | 1.5 | 2.9 | 2.6 | 0.0 | 4.1 | 2.9 |
1.9 | 2.4 | 0.0 | 1.8 | 3.1 | 3.8 | 3.2 | 1.6 | 4.2 | 0.0 |
1.2 | 1.8 | 2.4 |
(a) Use a calculator with mean and standard deviation keys to find x and s. (Round your answers to two decimal places.)
x = | % |
s = | % |
(b) Compute a 90% confidence interval for the population mean
μ of home run percentages for all professional baseball
players. Hint: If you use the Student's t
distribution table, be sure to use the closest d.f. that
is smaller. (Round your answers to two decimal
places.)
lower limit | % |
upper limit | % |
(c) Compute a 99% confidence interval for the population mean
μ of home run percentages for all professional baseball
players. (Round your answers to two decimal places.)
lower limit | % |
upper limit | % |
(d) The home run percentages for three professional players are
below.
Player A, 2.5 | Player B, 2.3 | Player C, 3.8 |
Examine your confidence intervals and describe how the home run percentages for these players compare to the population average.
We can say Player A falls close to the average, Player B is above average, and Player C is below average.
We can say Player A falls close to the average, Player B is below average, and Player C is above average.
We can say Player A and Player B fall close to the average, while Player C is above average.
We can say Player A and Player B fall close to the average, while Player C is below average.
(e) In previous problems, we assumed the x distribution
was normal or approximately normal. Do we need to make such an
assumption in this problem? Why or why not? Hint: Use the
central limit theorem.
Yes. According to the central limit theorem, when n ≥ 30, the x distribution is approximately normal.
Yes. According to the central limit theorem, when n ≤ 30, the x distribution is approximately normal.
No. According to the central limit theorem, when n ≥ 30, the x distribution is approximately normal.
No. According to the central limit theorem, when n ≤ 30, the x distribution is approximately normal.
Answer a)
Mean and Standard Deviation are calculated using MS Excel. Following is the screenshot:
x = | 2.29 % |
s = | 1.40 % |
Answer b)
90% Confidence Interval Calculation:
lower limit | 1.93 % |
upper limit | 2.65 % |
Answer c)
99% Confidence Interval Calculation:
lower limit | 1.71 % |
upper limit | 2.87 % |
Answer d)
The home run percentages for Player C is greater than upper limit of 99% Confidence Interval so Player C is above average
The home run percentages for Player A and B within 99% Confidence Interval Player A and Player B fall close to the average.
Correct Option is: "We can say Player A and Player B fall close to the average, while Player C is above average."
Answer e)
We do not need to make such an assumption in this problem because sample size is greater than 30
Correction Option is: "No. According to the central limit theorem, when n ≥ 30, the x distribution is approximately normal."