Statistics

Cramer’s V is used to measure the strength of association between two nominal (or categorical) variables. It’s often used in conjunction with the chi-square test of independence, which is used to determine whether or not two variables are independent of one another. By the end of this tutorial, you’ll have learned the following: What is […]

Being able to draw meaningful insights from data is an important skill. Statistical analysis is an important part of this process, which gives you tools to evaluate hypotheses and uncover trends in your data. Many statistical tests assume that your data are normally distributed, which may not always be the case. This is where the

In this post, you’ll learn how to perform t-tests in Python using the popular SciPy library. T-tests are used to test for statistical significance and can be hugely advantageous when working with smaller sample sizes. By the end of this tutorial, you’ll have learned the following: Understanding the T-Test The t-test, or often referred to

The Chi-Square Test of Independence tests for independence between two categorical variables. The test has many applications, from survey analysis to feature selection in machine learning. In this tutorial, you’ll learn how to calculate the chi-square test in Python using the SciPy library. By the end of this tutorial, you’ll have learned the following: What

Understanding the certainty and reliability of your data is essential in drawing meaningful conclusions. Confidence intervals give you a powerful statistical tool, which helps you estimate the range in which a population parameter, such as the mean, lies. In this tutorial, you’ll learn three different methods to calculate confidence intervals in Python. By the end

Levene’s test is an important statistical test used to assess the equality of variance between different samples. In this tutorial, you’ll learn how to understand and compute Levene’s test of equal variance in Python, using the important scipy package. Since many statistical tests work under the assumption that groups have equal variances, we can use

The coefficient of variation, or CV, allows you to measure how spread out values in a dataset are, relative to their mean. In this tutorial, you’ll learn how to interpret the coefficient of variation and how to calculate it in Python, including using SciPy, NumPy, and Pandas. Understanding the Coefficient of Variation The coefficient of