In Statistics, Pearson correlation coefficient is widely used to find out relationship among random variables. In this tutorial, we will learn to create a correlation matrix and represents using heat matrix.
Linear and Polynomial Regression in Python
Linear regression is the problem where a model(line) is built with available data and then learnt model is used to predict target value for future data. This is the most basic type of statistical method used for predictive analysis. In other words, it can be understood as finding a relationship between target value and the attributes of input data.The best model is where we get minimum error between predicted and actual values.
How to generate data with Gaussian noise for linear regression problem
In this post, We will learn how to generate noisy data points where Gaussian error is added. For the demonstration purpose, we will use python’s matplotlib and numpy modules.
Find out intersection points of two Gaussian distribution and calculate overlapping area
This post will provide tutorial on generating data from gaussian distribution, finding intersection data points and then computing overlapping area of two Gaussian distribution.