Answered: Can you explain the central limit…

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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Question

Can you explain the central limit theorem using the example of a group of coin flip trials (our population) where each trial has the same number of tosses (our sample size), and we are looking at the number of heads we get per trial, but increasing our sample size produces a normal distribution (because increasing the number of coin flips per trial decreases the likelihood that we will get extreme results on a trial--such as no heads or all heads)?

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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