Determine whether the following graph can represent a variable with a normal distribution. Explain your reasoning. If the graph appears to represent a normal distribution, estimate the mean and standard deviation. **Determine whether the following graph can represent a variable with a normal distribution. Explain your reasoning. If the graph appears to represent a normal distribution, estimate the mean and standard deviation.**![Graph]The graph shown is a symmetric, bell-shaped curve, characteristic of a normal distribution. It is centered near the value of 15 on the x-axis, with data tapering off symmetrically on both sides.**Could the graph represent a variable with a normal distribution? Explain your reasoning. Select the correct choice below and, if necessary, fill in the answer boxes within your choice.**- **A.** Yes, the graph fulfills the properties of the normal distribution. The mean is approximately [ ] and the standard deviation is about [ ].- **B.** No, because the graph crosses the x-axis.- **C.** No, because the graph is skewed right.- **D.** No, because the graph is skewed left.

Given, The graph of the variables which we want to examine it is normal or not.

Answered: Determine whether the following graph…

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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Determine whether the following graph can represent a variable with a normal distribution. Explain your reasoning. If the graph appears to represent a normal distribution, estimate the mean and standard deviation.

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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