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Statistics vocabulary · Regression and Correlation

Logistic regression

Meaning in statistics, with examples

nounCommon term

In statistics, logistic regression means: A regression method for an outcome with two categories, such as yes/no or pass/fail, that models the probability of one of the outcomes from the predictors.

In Turkish: lojistik regresyon

How it is used

Results are usually reported as odds ratios (OR) with confidence intervals: 'OR = 1.8, 95% CI [1.2, 2.7]'. Widely used in medicine, the social sciences and credit scoring. Extensions handle outcomes with more than two categories (multinomial or ordinal logistic regression).

Example sentences

  1. Logistic regression showed that smokers had higher odds of developing the condition (OR = 2.3).

  2. We used logistic regression to predict whether a customer would cancel their subscription.

Common collocations

  • binary logistic regression
  • odds ratio
  • fit a logistic regression
  • multinomial logistic regression
  • regressionA family of methods for modelling how an outcome variable changes with one or more predictor variables, used both to explain relationships and to make predictions.
  • dependent variableThe outcome a study measures to see whether it changes when the independent variable changes, such as test scores, sales or recovery time.
  • regression coefficientA number in a regression model showing how much the outcome is expected to change when a predictor increases by one unit, with the other predictors held constant.
  • multiple regressionA regression model with two or more predictor variables, used to estimate the effect of each one while holding the others constant.
  • categorical variableA variable whose values are groups or labels rather than measured quantities, such as blood type, city of residence or 'yes/no' answers.

More terms: Regression and Correlation

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