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close statistical will allow us to get an dispersion of ou data. The first measure is the variance, which measures how far from their mean the individua observations in our data are. The second is the standard deviation, which is the square root of the variance and measures the amount of variation or dispersion of a dataset. Write a function calculate_variance() that takes a list and returns its variance. The variance is calculated by first finding the mean (average), then by summing for all elements (element - mean)* and then dividing this sum to number of elements. Cs104 / ME202 Homework-3

close statistical will allow us to get an dispersion of ou data. The first measure is the variance, which measures how far from their mean the individua observations in our data are. The second is the standard deviation, which is the square root of the variance and measures the amount of variation or dispersion of a dataset. Write a function calculate_variance() that takes a list and returns its variance. The variance is calculated by first finding the mean (average), then by summing for all elements (element - mean)* and then dividing this sum to number of elements. Cs104 / ME202 Homework-3

Computer Networking: A Top-Down Approach (7th Edition)
Computer Networking: A Top-Down Approach (7th Edition)
7th Edition
ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
Section: Chapter Questions
Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Do not use numpy module or any other module.

language:PYTHON

Two closely related statistical measures will allow us to get an idea of the spread or dispersion of our data. The first measure is the variance, which measures how far from their mean the individual observations in our data are. The second is the standard deviation, which is the square root of the variance and measures the amount of variation or dispersion of a dataset. Write a function calculate_variance() that takes a list and returns its variance. The variance is calculated by first finding the mean (average), then by summing for all elements (element - mean)', and then dividing this sum to number of elements. cs104 / ME202 Homework-3 1 You can write another helper function called mean() that takes a list as parameter and returns its average. Write Python statements that create a list of one hundred elements with random integer values from 1-50, both inclusive. Display those values on the screen, calculate variance and standard deviation of your random dataset by calling the above explained functions and print the results. Do not use numpy module or any other module. Population Variance Sample Variance N n-1 ở - population variance x, -value of elamant = population mean N- population size - sample variace x, - value of " element * = sample mean - sample size Figure 1- You can implement one of the variance type.
Transcribed Image Text:Two closely related statistical measures will allow us to get an idea of the spread or dispersion of our data. The first measure is the variance, which measures how far from their mean the individual observations in our data are. The second is the standard deviation, which is the square root of the variance and measures the amount of variation or dispersion of a dataset. Write a function calculate_variance() that takes a list and returns its variance. The variance is calculated by first finding the mean (average), then by summing for all elements (element - mean)', and then dividing this sum to number of elements. cs104 / ME202 Homework-3 1 You can write another helper function called mean() that takes a list as parameter and returns its average. Write Python statements that create a list of one hundred elements with random integer values from 1-50, both inclusive. Display those values on the screen, calculate variance and standard deviation of your random dataset by calling the above explained functions and print the results. Do not use numpy module or any other module. Population Variance Sample Variance N n-1 ở - population variance x, -value of elamant = population mean N- population size - sample variace x, - value of " element * = sample mean - sample size Figure 1- You can implement one of the variance type.
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