Descriptive Statistics: Measures of Central Tendency and Measures of Dispersion

You have a data-set containing 10K data points where each data point is the house-hold income of a given area for example. But what do you with this data. The most fundamental tools that help in making sense of huge data-sets are "measures of Central Tendency" and "measure of Dispersion". They are also known as … Continue reading Descriptive Statistics: Measures of Central Tendency and Measures of Dispersion →

Types of Data or Types of Random Variables

We had discussed about the Random Variables previously with the help of examples "heights of people" (Hperson) and "outcome of a dice-roll"(Odice-roll). In both the cases the kind of values each of the random variables could take were different. The random variable Hperson can take any real-value between 0 feet and 15 feet while Odice-roll can only take one … Continue reading Types of Data or Types of Random Variables →

How to apply Mean and Standard Deviation?

Arithmetic Mean and Standard Deviation Formulae

What is Mean? Mean of any given distribution is a measure of central tendency of that distribution. Mean is also known as Arithmetic Mean or Average Value or Expected Value. For a data-set with discrete real values mean can simply be computed as sum of all the values in data-set divided by the number of … Continue reading How to apply Mean and Standard Deviation? →

Random Variables, Distribution function and Distribution Curve: A tutorial

Continuous Random Variable Distribution - Heights of people

What is a random Variable? Random Variables are a means of assigning numbers to outcomes of random processes or experiments or activities. An example of random variable can be an "outcome of rolling a dice". Let us denote this random variable by symbol "Odice-roll ". The values this random variable can take can be any … Continue reading Random Variables, Distribution function and Distribution Curve: A tutorial →

Hypothesis Testing with Controlled Experiments: Computing P-value using Z-statistic

Hypothesis testing with Normal Distribution

Google the word “experiment”, the answer returned is, “a scientific procedure undertaken to make a discovery, test a hypothesis, or demonstrate a known fact” While “Experiment” is a broader term, a controlled experiment specifically is about testing impact of a single factor /variable while the other variables remain constant. Confused? Don’t worry, read ahead. I … Continue reading Hypothesis Testing with Controlled Experiments: Computing P-value using Z-statistic →

A Primer on Machine Learning : Unsupervised Learning, Supervised Learning – Regression and Classification

Machine Learning high level summary. Supervised learning, classification, regression, unsupervised learning, clustering

1. What is Machine Learning? Machine learning is the ability of a computer to derive rules and patterns from given set of data. To derive these insights statistical tools are deployed through machine learning algorithms. Machine Learning algorithms break down the data (aka training data) to formulate best-fit mathematical models. Machine Learning can be broadly … Continue reading A Primer on Machine Learning : Unsupervised Learning, Supervised Learning – Regression and Classification →