Statistical - Inference

Thomas Bayes


Methods for drawing conclusions about a population from sample data

Two key methods

E.g., t-test – enables inferences about population beyond our data


Updating your beliefs by looking at the outside world is called “wiki/Bayesian inference

Discover More
Data System Architecture
Data (Analysis|Analyse|Analytics)

finding the right data to answer abusiness question, understanding the processes underlying the data, discovering the important patterns in the data, and then communicating your results to have...
Anscombe Regression
Machine Learning - (Supervised|Directed) Learning ( Training ) (Problem)

Supervised Learning has the goal of predicting a value (outcome) from particular characteristics (predictors) that describes some behaviour. The attribute used to trained and being predicted is called...
Card Puncher Data Processing

is a scientific discipline devoted to the study of data. is the art of extracting information from data. From Data to Information to Knowledge. No learning. lies lies, damned lies, and statistics....
Data System Architecture
Statistics - (Data|Data Set) (Summary|Description) - Descriptive Statistics

Summary are a single value summarizing a array of data. They are: selected or calculated through reduction operations. They are an important element of descriptive analysis One of the most important...
Thomas Bayes
Statistics - (Estimator|Point Estimate) - Predicted (Score|Target|Outcome| )

An estimator or point estimate is a statistic that is used to infer the value of an unknown parameter in a statistical model. A point is a value in this entire possible range of values from the distribution....
Overfitting Underfitting
Statistics - (Variance|Dispersion|Mean Square) (MS)

The variance shows how widespread the individuals are from the average. The variance is how much that the estimate varies around its average. It's a measure of consistency. A very large variance means...
Thomas Bayes
Statistics - Bayes’ Theorem (Probability)

Bayesian probability is one of the different interpretations of the concept of probability and belongs to the category of evidential probabilities. In the Bayesian view, a probability is assigned to a...
Thomas Bayes
Statistics - Causation - Causality (Cause and Effect) Relationship

Cause and Effect Relationship. Nothing beats a simple, elegant, controlled, randomized experiment if you want to make strong claims causality. Causal inference is a difficult and slippery topic, which...
Thomas Bayes
Statistics - Central limit theorem (CLT)

The Central_limit_theoremcentral limit theorem (CLT) is a probability theorem (unofficial sovereign) It establishes that when: random variables (independent) (estimate of a random process) are added...
Thomas Bayes
Statistics - Confidence Interval

The definition of a confidence interval says that under repeated experiments 95% of the time this confidence interval will contain the true statistic (mean, ...). if we started the whole experiment over...

Share this page:
Follow us:
Task Runner