A normal distribution, also known as Gaussian distribution or bell curve, is a continuous probability distribution that describes data with a symmetrical bell-shaped curve. It is widely used in statistics to model real-world phenomena, such as human height, IQ scores, and errors in measurement. In this tutorial, we will explore how to generate and plot…
A log-log plot, also known as a double logarithmic plot, is a useful visualization tool for analyzing data that follows a power law distribution. Power law distributions are characterized by the property that the probability of an event occurring is inversely proportional to the size of the event. In other words, large events are less…
Correlation is a statistical method used to measure the linear relationship between two variables. However, sometimes we want to know the relationship between two variables while controlling for the effect of a third variable. This is where partial correlation comes in. In this article, we will discuss the concept of partial correlation and how to…
Z-tests are a type of statistical hypothesis test used to determine if the population mean differs from a known value, called the hypothesized mean. This test is particularly useful when the population standard deviation is unknown and the sample size is large enough (n > 30). The null hypothesis, H₀, states that there is no…
Ready to take a spin on probability with Python? Let’s build a Monte Carlo simulation for a roulette wheel and visualize the possible outcomes as random walks. Buckle up! 1. Define the Model: A roulette wheel has 37 slots (European version): 18 red, 18 black, and 1 green (0). Your goal is to simulate placing…