## Frequency and Frequency Tables

The frequency of a particular data value is the number of times the data value occurs. For instance, on the off chance that four understudies have a score of 80 in arithmetic, and afterward the score of 80 is said to have a recurrence of 4. The recurrence of an information worth is frequently spoken […]

## An Intuitive (and Short) Explanation of Bayes’ Theorem

Testing is not the event. We have a test for cancer, which is separate from the event of actually having cancer. There is a test for spam, separate from the event of actually having a spam message. The tests are imperfect. Tests detect things that don’t exist (false positive), and things that exist are missing […]

## Margin of Error: Definition, How to Calculate in Easy Steps

Contents (click to skip to that section): What is a Margin of Error? How to Calculate Margin of Error (video) Margin of Error for a Proportion The margin of Error: Definition, How to Compute in Simple Advances Contents (snap to jump to that segment): What is a Margin of Error? Step by step instructions to […]

## Percentiles, Percentile Rank & Percentile Range: Definition & Examples

Statistics Definitions > Percentiles, Percentile Rank & Percentile Range Contents: Percentiles Percentile Rank How to Find a Percentile Percentile Range What are Percentiles? “Percentile” is in ordinary use, however, there is no all-inclusive definition for it. The most widely recognized meaning of a percentile is where a specific level of scores fall beneath that number. […]

## Multicollinearity

Multicollinearity is a state of very high interrelationships or interassociations between independent variables. It is a type of disturbance in the data, and if it is present in the data, the statistical inferences made on the data may not be reliable. There are some reasons why multi-linearity occurs: It is caused by inaccurate use of […]

## Sharpe Ratio

What Is the Sharpe Ratio? The Sharpe ratio was created by Nobel laureate William F. Sharpe and is utilized to assist financial specialists with understanding the arrival of speculation contrasted with its hazard. The proportion is the normal return earned in the overabundance of the hazard free rate per unit of unpredictability or absolute hazard. […]

## Simple guide to confusion matrix terminology

A confusion matrix is a table that is often used to describe the performance of a classification model (or “classifier”) on a set of test data for which the true values are known. The confusion matrix itself is relatively simple to understand, but the related terminology can be confusing. I needed to make a “brisk […]

## Causation vs Correlation – What’s the difference

Information in the right hands can be very incredible and ought to be a key component of any choice. One of the most axioms by an American analyst, W. Edwards Deming is, “In God we trust. Everyone else, bring data.” Be that as it may, over and over again than not, information can be misjudged […]

## Chapter 2 : SVM (Support Vector Machine) — Theory

Welcome to the second venturing stone of Supervised Machine Learning. Once more, this section is separated into two sections. Section 1 (this one) examines the hypothesis, working and tuning parameters. Section 2 (here) we take on little coding activity challenges. In the event that you haven’t read the Naive Bayes, I would propose you to […]

## Baffled by Covariance and Correlation???

Get the Math and the Application in Analytics for both the terms.. Covariance and correlation are two terms used significantly in the field of statistics and probability theory. The majority of articles and literature on probability and statistics presuppose a basic understanding of terms such as means, standard deviation, correlations, sample size and covariance.Let us […]