Binomial Distribution is used to find probabilities related to Dichotomous Population. It can be applied to a Binomial Experiment where it can result in only two outcomes. Success or Failure. In Binomial Experiments, we are interested in the number of Successes.
Binomial Probability Distribution Read More »
Probability Mass Function (PMF) of X says how the total probability of 1 is distributed (allocated to) among the various possible X values.
Probability Mass Function Read More »
Multiple Linear Regression Analysis with Categorical Predictors is done using Indicator Variables. We have to clearly analyze all possible models and select the best fitting model.
Multiple Linear Regression Analysis with Categorical Predictors Read More »
We use indicator variables when we have categorical variables in the Regression Equation. They are also known as Dummy Variables.
What are dummy variables in regression? Read More »
Multiple Linear Regression helps us to make predictions using two or more predictor variables. Concept of Multicollinearity is also very important in Regression Analysis.
Multiple Linear Regression Example Read More »
Linear regression is a way of modeling variables to make predictions. Here we discuss how can we do a simple linear regression analysis using Microsoft Excel.
Linear Regression in MS Excel Read More »
Expected Value is the average value we get for a certain Random Variable when we repeat an experiment a large number of times. It is the theoretical mean of a Random Variable. Expected Value is based on population data. Therefore it is a parameter.
Expected Value of a Random Variable Read More »
Simple Linear Regression is used to model the relationship between one predictor variable and one response variable. This is called ‘linear because the said relationship can be expressed in the form of the equation ‘y = mx + x”. And it is called ‘Simple’ because only one Predictor Variable is involved.
Simple Linear Regression Read More »
What is Regression Analysis? Regression Analysis is a Statistical Technique used to investigate and model the relationship between variables. It helps to identify trends associated with data and quantify them. In regression analysis, there are 2 main types of variables. Predictor Variable (Independent Variable) and Dependent Variable (Response Variable). For example, let’s say we use
Regression Analysis – Introduction Read More »
