## Performance Metrics of Classification Models

Performance metrics of Classification Model by Monisha Swami Chintu and Chutki have recently learned the concept of Classification. And they are all set to learn how to measure the model performance. Consider this example – Two new chocolate vending machines have been installed in the nearby shopping complex. The vending machine functions on the concept … Read more

## Unsupervised and Reinforcement Learning

Unsupervised and Reinforcement Learningby Monisha Swami Unsupervised Learning As the exams are approaching the teacher wants to take up extra classes where he is going to use different teaching techniques for different students to help them better. As one of the best ways to learn is by doing. The teacher provides Chintu and Chutki with … Read more

## Scales of Measurements

There are four scales on which a given variable can be measured – Nominal, Ordinal, Interval, Ratio. Nominal Scale Chintu has built several apps. All these apps have names. To handle the hosting, each app has also been allotted unique ID numbers. These apps cater to specific industries.  These three variables (name, ID, and industry) … Read more

## Evaluation Metrics – Linear Regression

A conceptual understanding of Linear Regression Analysis is a prerequisite for this article. Thus, we recommend you to visit this link if you need more clarity. Let’s begin! Evaluation Metrics of the Classical Linear Regression Model: Before understanding the metrics to assess model performance, let us understand why do we even need them?  A performance … Read more

## Summary of Discrete Statistical Distributions

A distribution is a statistical function that describes all the possible values and likelihoods that a random variable can take within a given range. (Ref: Statistical Models in Engineering, by Gerald Hahn and Samuel Shapiro, John Wiley and Sons, 1967) Binomial distribution It gives the probability of exactly x successes in n independent trials. Here, the probability … Read more

## Supervised Learning

How would you explain Supervised Learning to someone with no background in Statistics/ML? by Monisha Swami Chintu and Chutki share a great liking for chocolates. So every now and then the two of them visit a nearby chocolate vending machine. The machine accepts 1, 2, 5, and 10 rupee coins and vends the chocolates accordingly. … Read more

## Econometrics Basics for Interviews

In this blog, we have tried to explain multicollinearity, autocorrelation, and heteroscedasticity clearly. Why are there error terms in a model? You must have noticed the presence of an error term (ϵ, greek letter epsilon) in every statistical model. Below are the reasons for it: Usually, it is not possible to consider all the independent … Read more

## P-value and Level of Significance

At times understanding statistical concepts can be really tricky. One such concept is P-value. (You can look at the definition on Google. I could not understand it. Some of you might not be able to understand it unless you study Statistics like Anubhav Dubey :P).  Thus, Chintu and Chutki are here to explain it in … Read more