As an example of the multiple regression analysis discussed in the previous post, let's look at how to predict home prices using the California housing dataset. We'll walk through the process of loadi..

In today's data-driven world, making informed decisions is critical to success, and understanding regression analysis is a fundamental and important key to gaining valuable insights from your data. In..

 Bayes' theorem is a fundamental concept in probability theory, and can be thought of as a formula for finding conditional probabilities given some prior knowledge or data. In other words, we can..

We'll walk through the process of analyzing real-world sales data using probability distributions such as the normal distribution. Analyzing sales trends is the most common business use case, but it c..

Understanding correlation coefficients is crucial in business.It can be extended to identifying relationships, modeling forecasting and risk management to infer causality.1. Identify relationships:It ..

In the previous article we learned about the null hypothesis testing procedure.Link: http://tokenterrace.com/eng/212Let's implement it in Python code so that you can put the theory into practice.First..

 In the previous article, we discussed the null and alternative hypotheses. It gets a little boring when we get too theoretical, so let's look at a hypothesis testing scenario and create a h..

You've probably heard of independent and dependent variables in statistics, but do you know what they are and how they relate to each other?An independent variable is a variable that a researcher can ..

In truth, statistics has lost some of its significance as programming languages, machine learning, and deep learning have advanced. Of course, data scientists and analysts who examine data to comprehe..