Waiting times (in minutes) of customers at a bank where all customers enter a single waiting line and a bank where customers wait in individual lines at three differem teller windows are listed below. Find the coefficient of variation for each of the two sets of data, then compare the variation. Bank A (single line): 6.5 6.5 6.7 6.8 7.2 7.2 74 7.6 7.7 7.8 O Bank B (individual 4.4 5.3 5.8 6.2 6.8 7.7 7.7 8.5 9.3 9.7 lines): The coefficient of variation for the waiting times at Bank A is %. (Round to one decimal place as needed.) The coefficient of variation for the waiting times at the Bank B is %. (Round to one decimal place as needed.) Is there a difference in variation between the two data sets? O A. The waiting times at Bank A have considerably less variation than the waiting times at Bank B. O B. The waiting times at Bank B have considerably less variation than the waiting times at Bank A. O C. There is no significant difference in the variations.

Waiting times (in minutes) of customers at a bank where all customers enter a single waiting line and a bank where customers wait in individual lines at three differem teller windows are listed below. Find the coefficient of variation for each of the two sets of data, then compare the variation. Bank A (single line): 6.5 6.5 6.7 6.8 7.2 7.2 74 7.6 7.7 7.8 O Bank B (individual 4.4 5.3 5.8 6.2 6.8 7.7 7.7 8.5 9.3 9.7 lines): The coefficient of variation for the waiting times at Bank A is %. (Round to one decimal place as needed.) The coefficient of variation for the waiting times at the Bank B is %. (Round to one decimal place as needed.) Is there a difference in variation between the two data sets? O A. The waiting times at Bank A have considerably less variation than the waiting times at Bank B. O B. The waiting times at Bank B have considerably less variation than the waiting times at Bank A. O C. There is no significant difference in the variations.

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

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Concept explainers

Inverse Normal Distribution

The method used for finding the corresponding z-critical value in a normal distribution using the known probability is said to be an inverse normal distribution. The inverse normal distribution is a continuous probability distribution with a family of two parameters.

Mean, Median, Mode

It is a descriptive summary of a data set. It can be defined by using some of the measures. The central tendencies do not provide information regarding individual data from the dataset. However, they give a summary of the data set. The central tendency or measure of central tendency is a central or typical value for a probability distribution.

Z-Scores

A z-score is a unit of measurement used in statistics to describe the position of a raw score in terms of its distance from the mean, measured with reference to standard deviation from the mean. Z-scores are useful in statistics because they allow comparison between two scores that belong to different normal distributions.

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