Twelve different video games showing violence were observed. The duration times of violence were recorded, with the times (seconds) listed below. What requirements must be satisfied to test the claim that the sample is from a population with a mean greater than80 sec? Are the requirements all satisfied? 821456850052218401880256 What requirements must be satisfied? Select all that apply. A.The sample observations must be a simple random sample. B.Either the population is normally distributed, orn>30,or both. C.The conditions for a binomial distribution must be satisfied. D.At least one observation must be above or below80sec.

Answered: Twelve different video games showing…

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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Twelve different video games showing violence were observed. The duration times of violence were recorded, with the times (seconds) listed below. What requirements must be satisfied to test the claim that the sample is from a population with a mean greater than

80 sec? Are the requirements all satisfied?

568

218

188

What requirements must be satisfied? Select all that apply.

The sample observations must be a simple random sample.

Either the population is normally distributed, or

n>30,

or both.

The conditions for a binomial distribution must be satisfied.

At least one observation must be above or below

sec.

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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