ndependent random samples of professional football and basketball players gave the following information.Heights (in ft) of pro football players: x1; n1 = 456.316.516.506.256.506.336.256.176.426.336.426.586.086.586.506.426.256.675.916.005.836.005.835.086.755.836.175.756.005.756.505.835.915.676.006.086.176.586.506.256.335.256.656.505.85Heights (in ft) of pro basketball players: x2; n2 = 406.096.566.256.586.255.927.006.416.756.256.006.926.846.586.416.676.675.756.256.256.506.006.926.256.426.586.586.086.756.506.836.086.926.006.336.506.586.856.506.58 (a) Use a calculator with mean and standard deviation keys to calculate x1, s1, x2, and s2. (Round your answers to four decimal places.)x1 = s1 = x2 = s2 = (b) Let μ1 be the population mean for x1 and let μ2 be the population mean for x2. Find a 90% confidence interval for μ1 – μ2. (Round your answers to three decimal places.)lower limit upper limit

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Description: ndependent random samples of professional football and basketball players gave the following information.Heights (in ft) of pro football players: x1; n1 = 456.316.516.506.256.506.336.256.176.426.336.426.586.086.586.506.426.256.675.916.005.836.005.835

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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ndependent random samples of professional football and basketball players gave the following information.

Heights (in ft) of pro football players: x₁; n₁ = 45

6.31	6.51	6.50	6.25	6.50	6.33	6.25	6.17	6.42	6.33
6.42	6.58	6.08	6.58	6.50	6.42	6.25	6.67	5.91	6.00
5.83	6.00	5.83	5.08	6.75	5.83	6.17	5.75	6.00	5.75
6.50	5.83	5.91	5.67	6.00	6.08	6.17	6.58	6.50	6.25
6.33	5.25	6.65	6.50	5.85

Heights (in ft) of pro basketball players: x₂; n₂ = 40

6.09	6.56	6.25	6.58	6.25	5.92	7.00	6.41	6.75	6.25
6.00	6.92	6.84	6.58	6.41	6.67	6.67	5.75	6.25	6.25
6.50	6.00	6.92	6.25	6.42	6.58	6.58	6.08	6.75	6.50
6.83	6.08	6.92	6.00	6.33	6.50	6.58	6.85	6.50	6.58

(a) Use a calculator with mean and standard deviation keys to calculate x₁, s₁, x₂, and s₂. (Round your answers to four decimal places.)

x₁ =
s₁ =
x₂ =
s₂ =

(b) Let μ₁ be the population mean for x₁ and let μ₂ be the population mean for x₂. Find a 90% confidence interval for μ₁ – μ₂. (Round your answers to three decimal places.)

lower limit
upper limit

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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