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The F-Test for Regression Analysis

Towards Data Science

The F-test, when used for regression analysis, lets you compare two competing regression models in their ability to “explain” the variance in the dependent variable.

How Useful is F-test in Linear Regression?

Towards Data Science

Not very much, but we can improve it. Continue reading on Towards Data Science

How to do F-test in R | Compare variances in Rstudio

R-bloggers

The f-test in R is a powerful tool for comparing variances and drawing significant conclusions from your data. Understanding how to perform an F-test can transform your data analysis capabilities, all...

F1 to F-beta

Towards AI

Model Evaluation Image by Author F1 Score The F-1 score is a popular binary classification metric representing a balance between precision and recall. It is the Harmonic mean of precision and recall....

Hypothesis Testing

Analytics Vidhya

In any business scenario, any question can generally have two answers. Whenever we are faced with some problems, we have to make choices and to make those choices we use testing.

Testing

CherryPy Documentation and Tutorials

Testing To run the regression tests, first install tox: then run it To run individual tests type:

Testing

Matplotlib User's Guide

Testing Matplotlib uses the pytest framework. The tests are in lib/matplotlib/tests , and customizations to the pytest testing infrastructure are in matplotlib.testing . Requirements To run the tests ...

A/B Testing- part 2

Towards Data Science

This is the second post from my series on A/B testing. In part 1, we learned the idea behind an A/B test. In this post, I walk you through the statistics behind A/B testing and focus more on…

The Hypothesis Tester’s Appendix

Towards Data Science

If you’ve just read my article “Smart COVID-19 Decision-Making” and you’re used to classical statistical inference, you might notice I skipped a few steps. Let’s take a closer look by following along…...

STATISTICAL TESTS

Analytics Vidhya

Overview of most common Statistical tests. “STATISTICAL TESTS” is published by Kallepalliravi in Analytics Vidhya.

Chapter 28 - An Intro to Testing

Python 101

Python includes a couple of built-in modules for testing your code. They two methods are called doctest and unittest . We will look at how to use doctest first and in the second section we will intro...

The art of A/B testing

Towards Data Science

A/B testing is not only about splitting incoming traffic to different versions of a service. It is also about being able to interpret the results, using a solid statistics framework.

Comparison of F-test and mutual information

Scikit-learn Examples

Comparison of F-test and mutual information This example illustrates the differences between univariate F-test statistics and mutual information. We consider 3 features x_1, x_2, x_3 distributed unifo...

The Hypothesis Tester’s Guide

Towards Data Science

Hypothesis testing is the basis of classical statistical inference. It’s a framework for making decisions under uncertainty.

F-statistic: Understanding model significance using python

Analytics Vidhya

In statistics, a test of significance is a method of reaching a conclusion to either reject or accept certain claims based on the data. In the case of regression analysis, it is used to determine…

Essential Things You Need to Know About F1-Score

Towards Data Science

Learn about the key fundamentals of F1-score, one of the most important evaluation metrics in machine learning.

A/B Testing: The Case Study!

Towards Data Science

My previous blog gives a basic idea of what exactly is A/B testing. From the positioning of images on pages, to the checkout process, we are staunch advocates of A/B Testing. Knowledge of a concept…

The Most Important Statistical Test

Towards Data Science

The likelihood ratio test (LRT) “unifies” frequentist statistical tests. Brand-name tests like t-test, F-test, chi-squared-test, and so on are specific cases (or even approximations) of the LRT…

manual test

R-bloggers

manual test of post a simple way to visualize or summarize monthly returns as well as average monthly returns using R. Interested readers can modify the instrument, period and length of time to their ...

4 Essential A/B Testing Segments

Towards Data Science

In short, it’s good to think about your user base and specific segments that could influence your ML system (pre or post-deployment, but in this context, we’re more focused on post-deployment)…

A/B Testing 101 with Examples - A Summary of Udacity’s Course

Towards Data Science

Long before I took any statistical class, I’ve heard that A/B testing is almost a must for data analysts. So I Googled it and thought: Hmm…isn’t it just like the control and experiment studies we…

Testing

Python Packages

Testing is an important part of Python package development but one that is often neglected due to the perceived additional workload. However, the reality is quite the opposite! Introducing formal, au...

Hypothesis tests and p-value: a gentle introduction

Towards Data Science

Whenever statisticians are asked to make inference on some population parameters, which cannot be observed, they need to start from a representative sample of that population. However, once obtained…

The Three Types of A/B Tests

Towards Data Science

If you work in or around data you’ll likely know that the term data science is much contested. What it means and who gets to call themselves a data scientist is discussed, disputed, and mulled over…