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26. and Job Applicants Based on a Society for Human Resource Management survey, 36% of human resource professionals are at companies that rejected job candidates because of information found on their social media. If 25 human resource professionals are randomly selected, would 14 be a significantly high number to be at companies that rejected job candidates because of information found on their social media? Why or why not?

26. and Job Applicants Based on a Society for Human Resource Management survey, 36% of human resource professionals are at companies that rejected job candidates because of information found on their social media. If 25 human resource professionals are randomly selected, would 14 be a significantly high number to be at companies that rejected job candidates because of information found on their social media? Why or why not?

MATLAB: An Introduction with Applications
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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help with problem 26 using the 3 methods.

26. Social Media and Job Applicants Based on a Society for Human Resource Management survey, 36% of human resource professionals are at companies that rejected job candidates because of information found on their social media. If 25 human resource professionals are randomly selected, would 14 be a significantly high number to be at companies that rejected job candidates because of information found on their social media? Why or why not?
Transcribed Image Text:26. Social Media and Job Applicants Based on a Society for Human Resource Management survey, 36% of human resource professionals are at companies that rejected job candidates because of information found on their social media. If 25 human resource professionals are randomly selected, would 14 be a significantly high number to be at companies that rejected job candidates because of information found on their social media? Why or why not?
Method 1 Find the mean and standard deviation for the random variable, and then calculate how many standard deviations away from the mean the value falls. If the value is represented by X, and u is the mean and o is the standard deviation, then Χ - μ O ― = Z - Score would represent how many standard deviations away from the mean X falls. We called this the z-score for X. If this value is greater than or equal to 2, or less than or equal to -2, then we will consider the value X to be unusual. In other words, if X falls at least 2 standard deviations away from the mean we will consider it to be unusual. Method 2 Instead of calculating a z-score for X, use the mean and standard deviation of the distribution to calculate the values (μ-20) and (u + 20). If X is either less than or equal to (μ- 20) or greater than or equal to (u + 20), then we will consider X to be unusual. This is called the range rule of thumb. Method 3 Let X be the value of the random variable in question. Calculate the probability of obtaining a value more extreme than X relative to the mean. If X is greater than the mean, find the probability of obtaining a value greater than or equal to X, and if X is less than the mean, find the probability of obtaining a value less than or equal to X. If this probability is less than or equal to .05, then we will consider X to be unusual.
Transcribed Image Text:Method 1 Find the mean and standard deviation for the random variable, and then calculate how many standard deviations away from the mean the value falls. If the value is represented by X, and u is the mean and o is the standard deviation, then Χ - μ O ― = Z - Score would represent how many standard deviations away from the mean X falls. We called this the z-score for X. If this value is greater than or equal to 2, or less than or equal to -2, then we will consider the value X to be unusual. In other words, if X falls at least 2 standard deviations away from the mean we will consider it to be unusual. Method 2 Instead of calculating a z-score for X, use the mean and standard deviation of the distribution to calculate the values (μ-20) and (u + 20). If X is either less than or equal to (μ- 20) or greater than or equal to (u + 20), then we will consider X to be unusual. This is called the range rule of thumb. Method 3 Let X be the value of the random variable in question. Calculate the probability of obtaining a value more extreme than X relative to the mean. If X is greater than the mean, find the probability of obtaining a value greater than or equal to X, and if X is less than the mean, find the probability of obtaining a value less than or equal to X. If this probability is less than or equal to .05, then we will consider X to be unusual.
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