Statistics How To

Design of Experiments > Practice Effect Definition Practice effects are influences on test results when a test is taken more than once. As a simple example, a practice effects occurs when you take multiple practice SAT exams; practice can increase your overall score. However, in psychological and educational testing, the practice effect is usually an … Read more

Regression Analysis > Covariate What is a Covariate? In general terms, covariates are characteristics (excluding the actual treatment) of the participants in an experiment. If you collect data on characteristics before you run an experiment, you could use that data to see how your treatment affects different groups or populations. Or, you could use that … Read more

Statistics Definitions > Assumption of Independence What is the Assumption of Independence? The assumption of independence is used for T Tests, in ANOVA tests, and in several other statistical tests. It’s essential to getting results from your sample that reflect what you would find in a population. Even the smallest dependence in your data can … Read more

Statistics Definitions > McNemar Test Example What is the McNemar Test? The McNemar test is a non-parametric test for paired nominal data. It’s used when you are interested in finding a change in proportion for the paired data. For example, you could use this test to analyze retrospective case-control studies, where each treatment is paired … Read more

Statistics Definitions > Method of Moments You may want to read this article first: What are moments?. What is Method of Moments? The method of moments is a way to estimate population parameters, like the population mean or the population standard deviation. The basic idea is that you take known facts about the population, and … Read more

Design of Experiments > Criterion Validity What is Criterion Validity? Criterion validity (or criterion-related validity) measures how well one measure predicts an outcome for another measure. A test has this type of validity if it is useful for predicting performance or behavior in another situation (past, present, or future). For example: A job applicant takes … Read more

Statistics Definitions > What is Hierarchical Linear Modeling? Hierarchical linear modeling, also called multi-level modeling, is a way to analyze hierarchical data. Hierarchical data is data that is nested in some way. Nested data is a common occurrence in real life. For example: Employees are nested within departments, companies, geographic regions and sectors of the … Read more

Bias in Statistics > Assignment Bias What is Assignment Bias? Assignment bias happens when experimental groups have significantly different characteristics due to a faulty assignment process. For example, if you’re performing a set of intelligence tests, one group might have more people who are significantly smarter. Although this type of bias is usually associated with … Read more

Regression Analysis > Parsimonious Model What is a Parsimonious Model? Parsimonious models are simple models with great explanatory predictive power. They explain data with a minimum number of parameters, or predictor variables. The idea behind parsimonious models stems from Occam’s razor, or “the law of briefness” (sometimes called lex parsimoniae in Latin). The law states … Read more

Design of Experiments > What is a Block Plot A block plot helps you figure out what the most important factors in your experiment are, including interactions. A basic block plot will show if a factor is important. It will also show if that factor stays the same (i.e. if it is robust) for all … Read more