1-DV Data Type Cheat Sheet

This cheat sheet guides you through selecting the appropriate statistical test for a single dependent variable (1-DV) based on the measurement scale of the independent variable (IV) and the research question (differences vs. associations).

Core Principles

Identify the measurement scale of your independent variable (Nominal, Ordinal, Scale).
Determine if your research question aims to find differences between groups or associations between variables.
Consider the number of samples/groups involved (one or two).
Parametric tests are generally used for Scale data (Interval/Ratio) and assume normality.
Nonparametric tests are used for Nominal and Ordinal data, or when parametric assumptions are violated.
Related-samples designs involve measurements from the same group/sample at different times or conditions.
Independent-samples designs involve measurements from different groups/samples.

Key Terms

1-DV: Single Dependent Variable: The outcome variable being measured.
IV: Independent Variable: The variable manipulated or used to predict the DV.
Parametric Test: Statistical test assuming data follows a specific distribution (e.g., normal distribution).
Nonparametric Test: Statistical test that does not assume a specific data distribution.
Scale Data: Interval or Ratio data, allowing for meaningful calculation of means.
Ordinal Data: Data that can be ranked but has no fixed intervals between ranks.
Nominal Data: Categorical data with no inherent order.
Related-samples: Measurements taken from the same subjects under different conditions or at different times.
Independent-samples: Measurements taken from different, unrelated groups of subjects.
Correlational Design: Examines the relationship or association between two or more variables.
Experimental Design: Manipulates an IV to observe its effect on a DV, often involving control and experimental groups.