Now find ? + ?.Recall that ? represents the standard deviation. For a normal curve, as we have here, a point three standard deviations to the right of center will be located at the point where the curve is nearly touching the horizontal axis.Observing the graph of the normal curve we see that the point three standard deviations to the right of center is located atx = 91. Therefore, x = 88 is two standard deviations to the right of center and x = is one standard deviation to the right of center.We previously determined that ? = . So, ? + ? = . This image depicts a bell curve, also known as a normal distribution or Gaussian distribution. A normal distribution is a probability distribution that is symmetric around the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. In other words, the data is distributed in such a way that most of the observations cluster around the central peak and taper off symmetrically on either side.Key features of this normal distribution include:1. **Symmetry**: The curve is symmetric around the center, which in this graph is at the value of 82. This central value represents the mean of the dataset.2. **Bell Shape**: The shape of the graph resembles a bell, which is typical for this kind of distribution.3. **Data Spread**: The spread of the data is indicated by the horizontal axis values. The lines marked at 85, 88, and 91 represent specific data points.4. **Concentration**: Most of the data points lie closer to the mean (central value), and the frequency of the data points decreases as you move further away from the mean. This particular graph shows a slightly skewed distribution with data points marked at 82 (mean), and additional data points shown at 85, 88, and 91.Understanding normal distribution is fundamental in statistics as many statistical tests and methods assume data follows a normal distribution. It helps in determining probabilities and making inferences about the population from sample data.

Answered: Image /qna-images/answer/fdb31956-84d9-40b3-94d7-c025309e6389.jpg

Answered: Now find ? + ?. Recall that ?…

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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Now find

? + ?.

Recall that ? represents the standard deviation. For a normal curve, as we have here, a point three standard deviations to the right of center will be located at the point where the curve is nearly touching the horizontal axis.

Observing the graph of the normal curve we see that the point three standard deviations to the right of center is located atx = 91. Therefore, x = 88 is two standard deviations to the right of center and x = is one standard deviation to the right of center.
We previously determined that ? = . So, ? + ? = .

This image depicts a bell curve, also known as a normal distribution or Gaussian distribution. A normal distribution is a probability distribution that is symmetric around the mean, showing that data near the mean are more frequent in occurrence than data far from the mean. In other words, the data is distributed in such a way that most of the observations cluster around the central peak and taper off symmetrically on either side.

Key features of this normal distribution include:

1. **Symmetry**: The curve is symmetric around the center, which in this graph is at the value of 82. This central value represents the mean of the dataset.

2. **Bell Shape**: The shape of the graph resembles a bell, which is typical for this kind of distribution.

3. **Data Spread**: The spread of the data is indicated by the horizontal axis values. The lines marked at 85, 88, and 91 represent specific data points.

4. **Concentration**: Most of the data points lie closer to the mean (central value), and the frequency of the data points decreases as you move further away from the mean.

This particular graph shows a slightly skewed distribution with data points marked at 82 (mean), and additional data points shown at 85, 88, and 91.

Understanding normal distribution is fundamental in statistics as many statistical tests and methods assume data follows a normal distribution. It helps in determining probabilities and making inferences about the population from sample data.

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