Statistics How To

Statistics Definitions > 68 95 99.7 rule Contents: Empirical Rule (68 95 99.7 rule) Empirical Research What is the 68 95 99.7 rule? Watch the video or read on below: When you use a standard normal distribution (aka Gaussian Distribution):…

Types of Variables > Simply put, a measurement variable (sometimes called a numeric variable) expresses some type of measurement and has a number associated with it. For example: 12 cm, 5 feet, or 310 meters. The measured quantity doesn’t have…

Descriptive Statistics > Quadratic Mean / Root Mean Square What is the Quadratic Mean / Root Mean Square? The quadratic mean (also called the root mean square*) is a type of average. It measures the absolute magnitude of a set…

Regression Analysis > Quartic regression fits a quartic function (a polynomial function with degree 4) to a set of data. Quartic functions have the form: f(x) = ax4 + bx3 + cx2 + dx + e. For example: f(x) =…

Statistics Definitions > Sample spaces introduced in early probability classes are typically discrete. That is, they are made up of a finite (fixed) amount of numbers. For example, if you roll a die, the sample space (Ω) is [1, 2,…

Statistics Definitions > Shannon entropy (or just entropy) is a measure of uncertainty (or variability) associated with random variables. It was originally developed to weigh the evenness and richness of animal and plant species (Shannon, 1948). It’s use has expanded…

Statistics Definitions > Natural Numbers and Whole Numbers Contents (Click to skip to that section) Natural Number Whole Numbers Why Is a Natural Number a Whole Number? Whole Numbers Example Closed Sets and Wholes Properties of Whole numbers What is…

Statistics Definitions > What is Independence of Irrelevant Alternatives? Independence of Irrelevant Alternatives (IIA) is a condition that states that the relative likelihood of choosing from A from B won’t change if a third choice is placed into the mix.…

Regression Analysis > Additive Model and Multiplicative Model in Regression The additive model and multiplicative model are generalizations of the “usual” linear regression model (Hastie & Tibshirani, 1990). The additive model is the arithmetic sum of the predictor variables‘ individual…

Bayesian Statistics and Probability > A prior distribution represents your belief about the true value of a parameter. It’s your “best guess.” One you’ve done a few observations, you recalculate with new evidence to get the posterior distribution. Formally, the…