# Logistic Regression – Basics

Logistic Regression can be binary or multi-nomial depends on the no of levels hold by response variable. Here we will discuss Binary Logistic Regression but same things are applied for multi-nomial as well. What is Binary Logistic Regression? Binary Logistic regression means response variable will have two values (either 1 or 0). It is a special[…]

# Relation between Correlation and Linear Regression

As these two terms looks similar Correlation and linear regression  but actually they are not. They both defines the relationship between two variables. Lets see how they are different: Linear regression finds the model (best fitted line) that can best predict the value of Y using value of X. Measure for fit for regression model[…]

# Linear Regression

What is Linear Regression? It is a predictive analysis technique. With this technique we can predict a variable called as response variable (or dependent variable) using one or more explanatory variables (or independent or predictor variables). When there is only one predictor variable, then method is called as simple regression otherwise multiple regression. Linear regression consists[…]

# What is Central Limit theorem?

In probability theory, the central limit theorem states that if the population is normally distributed then samples will also be normally distributed for any sample size. But if population is not normal then sample will be normally distributed if sample (of size n) are drawn randomly from a population that has a mean of µ[…]

# What are Type I and Type II errors?

In a statistical hypothesis test, there are two types of incorrect conclusions that can be drawn. The hypothesis can be inappropriately rejected (this is called type I error), or one can inappropriately retain the hypothesis (this is called type II error). The Greek letter α is used to denote the probability of type I error,[…]

# Difference between stratified and cluster sampling?

Basically in a stratified sampling procedure, the population is first partitioned into disjoint classes (the strata) which together are exhaustive. Thus each population element should be within one and only one stratum. Then a simple random sampling technique is applied and samples are taken out from each stratum for the final sample. This can be[…]

# What is p-value in statistics?

It is a way of quantifying the strength of the evidence against the null hypothesis and in favors of the alternative. P-value quantifies how strongly the data favor HA over H0. It can be said to be a conditional probability. If H0 is true, then the probability of observing large sample mean will be low.[…]

# Properties of a Normal Distribution Model

Also known as “Gaussian distribution” or “bell curve”. Symmetric: If curve is divided into 2 equal parts then one half will be similar to other half. Unimodel: It will have only 1 mode. Mean=Median=Mode (All 3 will be equal). It is said that nor distribution “Curve will never touch x-axis”. Total Area under the curve[…]