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# Statistics for Data Science

## Data Sciences Interview preparation

The measure of central tendency and dispersion Central tendency is the way to describe the centermost value of the data set i.e. it describes where the maximum values lie. The 3 ways to calculate central tendency are: Mean: it is

## Excel – Descriptive Statistics

Today, we have data all around with millions of new data points being generated every second. Everyone, a company, an individual, is using data to derive inferences and insights that can be useful. Statistics are crucial for working on any

## Bayesian Inference in Python

Bayes Theorem Bayes Theorem uses prior knowledge or experience to provide better results. Mathematically speaking, it uses conditional probability of an eventBayes’ theorem is stated mathematically as the following equation: P(A/B) =…

## Correlation Analysis Using R

Do you come across questions like, "Is X related to Y?”. Such questions are common in almost every sphere, right from knowing the relation between the income and education to the relation between no. of hours studied and marks in the exam.

## Actuarial Science: Graduation and Statistical Test

In this article, we will talk about Graduation and Statistical Test. Every business is done with the motive to earn a profit and accordingly, the price of products or services are charged. Likewise, for insurance companies premium is the

## Theory of Estimation Or What is Estimation

One of the major applications of statistics is to estimate the unknown population parameter. For example what is Estimation, a poll may seek to estimate the portion of adult residents of a city who are unemployed. The process of providing

## Information Value (IV) and Weight of Evidence (WOE)

In this article, we will learn more about the Information Value (IV) and Weight Of Evidence (WOE). The logistic regression model is one of the most commonly used statistical techniques for solving binary classification problem. It is…

## Queueing Theory and Its Application

Introduction In this article, we will learn about Queueing Theory and its practical applications. We all have experienced the annoyance of having to wait in a queue. We wait in line at supermarkets to check out, we wait in line in banks and…

## Data Visualization in Statistics and Data Science

In this Data Visualization article, we will cover some basics and important ways of Data Presentation. When it comes to the burning topic of Data Science, information from Data collected in a raw format isn’t easily comprehensible and is…

## Obtaining A Critical Region And p-Value

In this article, we will discuss how important obtaining a critical region is in the analytical and data science problem-solving. The critical region is the set of all values of the test statistic that causes us to reject the null…