# Q-Step Glossary

Do you know your causation from your correlation? Here are some of the most commonly used statistical terms in the Q-Step programme, which teaches social scientists how to quantify and measure ideas. If the term you are looking for is not here, please contact us at This email address is being protected from spambots. You need JavaScript enabled to view it.

The idea that a change in an independent variable changes the value of a dependent variable.

A set of rules or instructions to tell your computer what you want it to do.

A room offering access to computing resources, where students will learn how to write code in R to analyse data to answer social scientific questions.

An unknown value that does not vary.

A measure of linear association between two variables. Correlation is not the same as causation.

Facts from which conclusions can be drawn.

The variable whose values are supposed to be explained by changes in the independent variables.

The difference between between an observed and predicted value of the dependent variable.

A rule for calculating an estimate of a parameter. For instance, OLS is an estimator for the regression coefficients.

The variable that is supposed to explain changes in the dependent variable.

A statistical model that represents a continuous dependent variable as a linear function of the parameters (regression coefficients) and the independent variables plus an error term that follows a normal distribution. The regression coefficients are usually estimated via OLS. For instance, one might say that income depends on education plus chance events. Expressed as a linear regression model this would mean that income = a + b*education + e, where a is a constant, b is the regression coefficient of Education, and e is the error term.

An idealised representation of the process that generated the the values of the dependent variable.

A symmetric, bell-shaped distribution.

An estimator that minimises the sum of squared errors.

An unknown quantity such as the population mean.

A free software environment for statistical computing and graphics.

An estimate of how much a one-unit increase in the independent variable is associated with changes in the dependent variable.

A function showing all possible values of the variable and their relative frequency.

A member of a population. For instance, a voter (unit) is a member of the electorate (population).

A numerical value that can differ across units. For instance, voter's age (variable) can be 18 years, 19 years, and so on.