The weights (in pounds (lb)) of 52 randomly selected NFL football players are presented below.305 265 287 285 290 235 300 230 195 236 244 194 190 307 218 315 265 210 194 216 255 300 315 190 185 183 313 246 212 201 308 270 241 242 306 237 315 215 200 295 187 204 257 185 255 318 230 316 200 324 245 185We would like to construct a 90% confidence interval for the mean weight of NFL football players.Explain why it is not necessary to assess normality for this sample Write an interpretation for your confidence interval, including units if appropriate. You may round the upper and lower limits to the nearest whole number.Does the confidence interval estimate the mean weight for the sample of 52 NFL players or for the population of NFL players? Explain.

The objective is to estimate the average weight of NFL players with a certain level of surety in the…

Answered: The weights (in pounds (lb)) of 52…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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The weights (in pounds (lb)) of 52 randomly selected NFL football players are presented below.

305 265 287 285 290 235 300 230 195 236 244 194 190 307 218 315 265 210 194 216 255 300 315 190 185 183 313 246 212 201 308 270 241 242 306 237 315 215 200 295 187 204 257 185 255 318 230 316 200 324 245 185

We would like to construct a 90% confidence interval for the mean weight of NFL football players.

Explain why it is not necessary to assess normality for this sample
Write an interpretation for your confidence interval, including units if appropriate. You may round the upper and lower limits to the nearest whole number.
Does the confidence interval estimate the mean weight for the sample of 52 NFL players or for the population of NFL players? Explain.

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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