Probability Distributions > The g-and-h distribution (a combination of the g-distribution and h-distribution*) is used in statistical modeling as an alternative for Ordinary Least Squares. Developed by Tukey in 1977, it is seldom used perhaps because it does not have…

Statistics Definitions > Binomial coefficients tell us how many ways there are to choose k things out of larger set. More formally, they are defined as the coefficients for each term in (1+x)n. Written as , (read n choose k),…

Statistics Definitions > You may want to read this article first: What is a Factorial(!)? The multinomial coefficient, used in combinatorics, is an extension of the binomial coefficient. It’s used to find permutations when you have repeating values or duplicate…

Statistics Definitions > The minimal detectable difference is the smallest difference, or change, that can be statistically detected in a given study. It  is  dependent on your desired significance level, and has been defined as the smallest difference δ where…

Statistics Definitions > An active variable is a variable that is manipulated by the investigator. It’s designed to shine light on some part of a question or problem, and its usefulness comes in the way it can be controlled by…

Hypothesis Tests > The Chi-Square Test for Normality allows us to check whether or not a model or theory follows an approximately normal distribution. The Chi-Square Test for Normality is not as powerful as other more specific tests (like Lilliefors).…

Statistics Definitions > Real numbers are any numbers that can be represented on the number line. The set of real numbers (also called the reals) includes both the set of rational numbers (numbers that can be written as ratios or…

Statistics Definitions > A trimean is a number that represents the general tendency of a set of numbers or data set. Like the mean, median, and mode, it is a measure of central tendency. It is defined to be the…

Statistics Definitions > A ranked variable is an ordinal variable; a variable where every data point can be put in order (1st, 2nd, 3rd, etc.). You may not know an exact value of any of your points, but you know…

Regression Analysis > Relative Weights What are Relative Weights? Johnson’s Relative Weights is a way quantify the relative importance of correlated predictor variables in regression analysis. “Relative importance” in this context means the proportion of the variance in y accounted…