Suppose a sample of O-rings was obtained and the wall thickness (in inches) of each was recorded. Use a normal probability plot to assess whether the sample data could have come from a population that is normally distributed. 0.186 0.205 0.255 0.305 0.191 0.212 0.266 0.298 0.188 0.222 0.278 0.307 0.197 0.246 0.290 0.311 Yes. The correlation between the expected z-scores and the observed data, nothing, exceeds the critical value, nothing. Therefore, it is reasonable to conclude that the data come from a normal population. B. Yes. The correlation between the expected z-scores and the observed data, nothing, exceeds the critical value, nothing. Therefore, it is not reasonable to conclude that the data come from a normal population. C. No. The correlation between the expected z-scores and the observed data, nothing, does not exceed the critical value, nothing. Therefore, it is reasonable to conclude that the data come from a normal population. D. No. The correlation between the expected z-scores and the observed data, nothing, does not exceed the critical value, nothing. Therefore, it is not reasonable to conclude that the data come from a normal population.

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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Suppose a sample of O-rings was obtained and the wall thickness (in inches) of each was recorded. Use a normal probability plot to assess whether the sample data could have come from a population that is normally distributed.

0.186
0.205
0.255
0.305
0.191
0.212
0.266
0.298
0.188
0.222
0.278
0.307
0.197
0.246
0.290
0.311

Yes.

The correlation between the expected z-scores and the observed data,

nothing,

exceeds

the critical value,

nothing.

Therefore, it is

reasonable

to conclude that the data come from a normal population.

Yes.

The correlation between the expected z-scores and the observed data,

nothing,

exceeds

the critical value,

nothing.

Therefore, it is

not reasonable

to conclude that the data come from a normal population.

No.

The correlation between the expected z-scores and the observed data,

nothing,

does not exceed

the critical value,

nothing.

Therefore, it is

reasonable

to conclude that the data come from a normal population.

No.

The correlation between the expected z-scores and the observed data,

nothing,

does not exceed

the critical value,

nothing.

Therefore, it is

not reasonable

to conclude that the data come from a normal population.

Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.

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