Calculating Standard Deviation in Python: A Comprehensive Guide
In Python, Standard Deviation can be calculated in many ways – learn to use Python Statistics, Numpy’s, and Pandas’ standard deviant (std) function.
Statistics
Numpy Normal (Gaussian) Distribution (Numpy Random Normal)
In this tutorial, you’ll learn how to use the Numpy random.normal function to create normal (or Gaussian) distributions. The functions provides you with tools that allow you create distributions with specific means and standard distributions. Additionally, you can create distributions
How to Calculate Mean Squared Error in Python
The mean squared error is a common way to measure the prediction accuracy of a model. In this tutorial, you’ll learn how to calculate the mean squared error in Python. You’ll start off by learning what the mean squared error
How to Calculate a Z-Score in Python (4 Ways)
In this tutorial, you’ll learn how to use Python to calculate a z-score for an array of numbers. You’ll learn a brief overview of what the z-score represents in statistics and how it’s relevant to machine learning. You’ll then learn
Calculate and Plot a Correlation Matrix in Python and Pandas
In this tutorial, you’ll learn how to calculate a correlation matrix in Python and how to plot it as a heat map. You’ll learn what a correlation matrix is and how to interpret it, as well as a short review
Relative Frequencies and Absolute Frequencies in Python and Pandas
In this post, you’ll learn how to calculate relative frequencies and absolute frequencies using pure Python, as well as the popular data science library, Pandas. A relative frequency, measures how often a certain value occurs in a dataset, relative to