bayes theorem this is another rule or theorem which is useful when we know the probability of an event of interest ( )the conditional probability for another event based on our event of interest ( aand we want to determine the conditional probability of our event of interest given the other event has taken place ( bthis can be defined mathematically using the following expression ( ) ap (bsuch that and are events and ap statistics the field of statistics can be defined as specialized branch of mathematics that consists of frameworks and methodologies to collectorganizeanalyzeinterpretand present data generally this falls more under applied mathematics and borrows concepts from linear algebradistributionsprobability theoryand inferential methodologies there are two major areas under statistics that are mentioned as follows descriptive statistics inferential statistics the core component of any statistical process is data hence typically data collection is done firstwhich could be in global termsoften called population or more restricted subset due to various constraints often knows as sample samples are usually collected manuallyfrom surveysexperimentsdata storesand observational studies from this datavarious analyses are carried out using statistical methods descriptive statistics is used to understand basic characteristics of the data using various aggregation and summarization measures to describe and understand the data better these could be standard measures like meanmedianmodeskewnesskurtosisstandard deviationvarianceand so on you can refer to any standard book on statistics to deep dive into these measures if you're interested the following snippet depicts how to compute some essential descriptive statistical measures in [ ]descriptive statistics import scipy as sp import numpy as np get data nums np random randint( , size=( , ))[ print('data'numsget descriptive stats print ('mean:'sp mean(nums)print ('median:'sp median(nums)print ('mode:'sp stats mode(nums)print ('standard deviation:'sp std(nums)print ('variance:'sp var(nums)print ('skew:'sp stats skew(nums)print ('kurtosis:'sp stats kurtosis(nums)