Paolo Gironi - appunti di analisi dei dati,seo,statistica, retroinformatica

The Negative Binomial Distribution (or Pascal Distribution)

The negative binomial distribution describes the number of trials needed to achieve a certain number of successes in a series of independent trials. For example, it could be used to calculate the probability of getting three heads when flipping a coin 5 times, assuming the coin is balanced and therefore the probability of getting heads on each flip is 50%.

The negative binomial distribution is useful in many fields, including statistics, economics, biology, and physics. And also in “our” SEO.

First Steps into the World of Probability: Sample Space, Events, Permutations, and Combinations

Probability and combinatorics are two fundamental concepts in mathematics and statistics that help us understand and interpret many phenomena in everyday life. In this introductory post, we’ll “touch upon” the main concepts together, seeing how they can be applied in various contexts.

Logistic Regression: Predicting the Outcome of an Event

Logistic regression is a statistical model used to predict the probability of an event based on a set of independent variables. It’s particularly useful when you want to classify an event as belonging or not to a specific category (for example, whether a customer will buy a product or not, or whether a patient will develop a disease or not).

It is a Supervised Machine Learning algorithm that can be used to model the probability of a specific class or event. It is used when the data is linearly separable – that is, if there exists a line or plane that can be used to uniquely separate the data into different classes – and the outcome is binary or dichotomous. This means that logistic regression is typically used for binary classification problems (Yes/No, Correct/Incorrect, True/False, etc.),

In this post, I will demonstrate how to perform binomial logistic regression to create a classification model, in order to predict binary responses on a given set of predictors.

Non-Parametric Tests: The Wilcoxon Test for Non-Normal Data

The Wilcoxon test is a non-parametric test used to compare two independent samples, or a sample with a known reference value.
The test is used when the data do not follow a normal distribution, or when the distribution parameters are unknown.