rite a function that calculates the mean, median, variance, standard deviation, minimum and maximum of of list of items. You can assume the given list is contains only numerical entries, and you may use numpy functions to do this. Function Specifications: Function should allow a list as input. It should return a dict with keys 'mean', 'median', 'std', 'var', 'min', and 'max', corresponding to the mean, median, standard deviation, variance, minimum and maximum of the input list, respectively. The standard deviation and variance values must be unbiased. Hint: use the ddof parameter in the corresponding numpy functions! All values in the returned dict should be rounded to 2 decim
rite a function that calculates the mean, median, variance, standard deviation, minimum and maximum of of list of items. You can assume the given list is contains only numerical entries, and you may use numpy functions to do this. Function Specifications: Function should allow a list as input. It should return a dict with keys 'mean', 'median', 'std', 'var', 'min', and 'max', corresponding to the mean, median, standard deviation, variance, minimum and maximum of the input list, respectively. The standard deviation and variance values must be unbiased. Hint: use the ddof parameter in the corresponding numpy functions! All values in the returned dict should be rounded to 2 decim
C++ for Engineers and Scientists
4th Edition
ISBN:9781133187844
Author:Bronson, Gary J.
Publisher:Bronson, Gary J.
Chapter6: Modularity Using Functions
Section6.1: Function And Parameter Declarations
Problem 10E
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Write a function that calculates the mean, median, variance, standard deviation, minimum and maximum of of list of items. You can assume the given list is contains only numerical entries, and you may use numpy functions to do this.
Function Specifications:
- Function should allow a list as input.
- It should return a dict with keys 'mean', 'median', 'std', 'var', 'min', and 'max', corresponding to the mean, median, standard deviation, variance, minimum and maximum of the input list, respectively.
- The standard deviation and variance values must be unbiased. Hint: use the ddof parameter in the corresponding numpy functions!
- All values in the returned dict should be rounded to 2 decimal places.
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