Linear Regression in Statistics

Calculation-for-Regression-Line

Linear regression Linear regression refers to find out degree of relationship between two variables in the form of a linear function y=mx+c using statistical techniques. Where m is gradient and c is intercept on y axis. That best fits the data set, which predicts the value of y for a given x or vice versa. … Read more Linear Regression in Statistics

Poisson Distribution as a Limiting Case of Binomial Distribution

For large value of n binomial distribution asymptotically tends to Poisson distribution. Probability distribution  function of binomial random variable  is Probability distribution of Poisson random variable is Poisson Distribution as a Limiting Case of Binomial Distribution Python Code for Binomial Distribution from scipy.stats import binom import numpy as np import matplotlib.pyplot as plt # Let … Read more Poisson Distribution as a Limiting Case of Binomial Distribution

Exponential Probability Distribution

Mean of Exponentially Distributed Random Variable X

A random variable X is said to follow exponential distribution if it follows the following probability mass function. Exponential probability distribution is a continuous distribution. Probability Distribution Function of Exponentially Distributed Variable X   It is heavily used in the Internet traffic modelling and of study queuing models. Numerical Example- Problem- If a computer receives … Read more Exponential Probability Distribution

Poisson Distribution in Statistics

Mean of Poisson Distribution Variable X

A random variable X is said to follow Poisson distribution, if it follows the following probability distribution function. Poisson distribution is a discrete probability distribution. It models the following types of problems Find out number  of new born babies in a city in certain time duration. Find out defective materials in manufactured by a company. … Read more Poisson Distribution in Statistics

Binomial Distribution in Statistics

Expectation of X in Binomial Distribution

Let X be a random variable, it is said to follow binomial distribution if it follows the following probability mass function. And it can have only non-negative values. The binomial distribution is a discrete probability distribution. Binomial distribution is used to model problems, for instance,  getting  number of success after certain  number of random experiments … Read more Binomial Distribution in Statistics

Uniform Distribution

Uniform-Distributionsize5000.png

Uniform Distribution or Rectangular Distribution Uniform distribution or rectangular distribution is a continuous probability distribution. Definition- A random variable X is said to follow uniform or rectangular distribution it follows the following probability distribution function. And is denoted by X~U(a,b) Python Code to Plot Uniform Distribution import numpy import matplotlib.pyplot as plt a=20 b=50 x= … Read more Uniform Distribution

Central Limit Theorem and Normal Distribution

Area Under Normal Distribution Curve

  Why is normal distribution is important? To understand the question you have to go through the Central Limit Theorem. Central Limit Theorem According to central limit theorem if X1, X2, X3,……Xn are random variables drawn from any probability distribution function with mean  Σμi  and standard deviation Σσi where (i=1,2,3,……n). The sum of random variables … Read more Central Limit Theorem and Normal Distribution

Correlation in Statistics

Spearman Rank Correlation

Correlation Correlation measures  the relation between two variables  that how they are related.  And is denoted by r and  ρ moreover, the correlation quantifies the level of relationship between -1 to +1. If the value of correlation  r is -1 then there is perfect negative relationship. If value of  correlation is  +1  then there is … Read more Correlation in Statistics

Standard Deviation, Variance and Covariance

Standard Deviation

Standard Deviation Variance and Covariance Standard deviation, variance and covariance have very important applications in machine learning and data science. Further, they are closely related to each other. In feature reduction techniques, such as PCA ( Principle Component Analysis) features are selected based on  high variance.  In this post I will explain standard deviation, variance … Read more Standard Deviation, Variance and Covariance

Skewness and Kurtosis

Skewness and Kurtosis- Introduction- Skewness and Kurtosis are very important  concepts in statistics and have several applications.  In addition, they characterize the nature of data distribution which make data analysis easier. Moreover, I will separately discuss skewness and kurtosis in further sections. Skewness- Skewness  refers the measurement of lack of symmetry in data distribution. Measures … Read more Skewness and Kurtosis