# Statistics

## Classical Method of Time Series Analysis

The classical method of time series is done by decomposing a time series into trend, seasonal, cyclic and irregular components. What is decomposing? The meaning of the word “decomposing” in Mathematics is breaking something into parts, that together are the same as the original. For example, we can decompose 664 like this; 664 –> 600 […]

## Time Series Analysis

Introduction Most of you have heard about the term Time Series Analysis if you have learned Statistics as a subject anywhere. We at datasciencelk, are bringing you a series of posts about Time Series Analysis in detail. So what actually is Time Series Analysis? Time Series Analysis is basically the study and forecasting of time

## Poisson Distribution Explained

Poisson Distribution outputs the probability of a sequence of events happening in a fixed time interval.

## Uniform Probability Distribution

In a Uniform Distribution Probability Density Function (PDF) is same for all the possible X values. Sometimes this is called a Rectangular Distribution. There are two (2) parameters in this distribution, a minimum (A) and a maximum (B)

## Normal Distribution, Z Scores and Standardization Explained

Normal Distribution is the most important probability distribution in Probability and Statistics. A normal probability distribution is a bell shaped curve. Many numerical populations have distributions that can be fit very closely by an appropriate normal curve.

## Probability Density Function

Earlier we used Probability Mass Function to describe how the total probability of 1 is distributed among the possible values of the Discrete Random Variable X.

## Estimation of Best Fitting Line

Estimation of model parameters is an essential part in regression analysis. We do that by using the Ordinary Least Squares method

## Random Variables in Statistics

A Random Variable is any rule that maps (links) a number with each outcome in sample space S. Mathematically, random variable is a function with Sample Space as the domain. It’s range is the set of Real Numbers.

## Negative Binomial Distribution

In the Negative Binomial Distribution, we are interested in the number of Failures in n number of trials. This is why the prefix “Negative” is there. When we are interested only in finding number of trials that is required for a single success, we called it a Geometric Distribution.