Probability and Statistics - Statistical Measures
Table of Content:
Probability and Statistics - Statistical Measures
In this scenario, you will be exploring the most commonly used statistical measures
1. Mean
2. Median
3. Standard Deviation
4. Variance
5. Mode
6. Inter Quartile Range
Function Description
Function Name: measures()
1. Input:
arr - Numpy array
2. Output:
mean,median,std_deviation,variance,mode,iqr : tuple of results
Note: Every value must be rounded off to 2 decimal places
Sample Input For Custom Testing
4
1
2
4
4
Sample Output
(2.75, 3.0, 1.3, 1.69, 4.0, 2.25)
Explanation
Mean=2.75
Median=3.0
Standard Deviation=1.3
Variance=1.69
Mode=4.0
Inter-quartile Range=2.25
import numpy as np from scipy import stats import statistics def measures(arr): #Write your code here ''' Input: arr : numpy array Return : mean,median,std_deviation,variance,mode,iqr : float Note: 1. Assign the values to designated variables 2. Round off to 2 decimal places ''' mean = round(np.mean(arr), 2) median = round(np.median(arr), 2) std_deviation = round(np.std(arr), 2) variance = round(np.var(arr), 2) mode = round(stats.mode(arr)[0][0], 2) q1, q3 = np.percentile(arr, [25, 75]) iqr = round(q3 - q1, 2) return mean,median,std_deviation,variance,mode,iqr if __name__=='__main__': array1=[] n=int(input()) for i in range(n): array1.append(float(input())) narray1=np.array(array1) print(measures(narray1))