Choosing the Right Statistical Test

Flashcards covering key concepts from the lecture on how to choose the right statistical test for data analysis.

Statistical Conclusion Validity

The degree to which conclusions about the relationship among variables based on the statistical analyses are correct.

Causal Designs

Research designs that compare groups to establish cause and effect relationships.

Relational Designs

Research approaches that explore the associations or correlations between variables without manipulating them.

Correlation Does Not Equal Causation

A principle stating that correlation between two variables does not imply that one causes the other.

Independent Variable

A factor that is manipulated in an experiment to determine its effect on a dependent variable.

Dependent Variable

The outcome variable that researchers measure to assess the effects of the independent variable.

Between Subjects Design

An experimental design where different participants are assigned to each group.

Within Subjects Design

An experimental design where the same participants are used in all groups.

Statistical Assumptions

Basic conditions that need to be met for the results of a statistical analysis to be valid.

Normality

Refers to the data being distributed in a bell-shaped curve.

Homogeneity of Variance

The assumption that different samples have similar variances.

Independence Assumption

The assumption that each participant's data is independent of others.

Parametric Statistics

Statistical techniques based on assumptions about the population distribution and require interval or ratio data.

Non-parametric Statistics

Statistical tests that do not assume a specific distribution and are used for ordinal or nominal data.

Matched Pairs Design

A research design where pairs of participants are matched on certain characteristics.

Multiple Regression

A statistical method that models the relationship between one dependent variable and two or more independent variables.

Logistical Regression

A statistical method used to model outcomes that are binary or dichotomous.

Discriminant Analysis

A statistical technique used to classify observations into predefined classes.

Predictive Model

A method used to predict future outcomes based on current data.

Complex Comparison Chart

A tool used to determine appropriate statistical tests when dealing with more than one independent variable.

Basic Relational Statistics

Analyzes how two variables relate to each other in a non-causal manner.

Complex Relational Statistics

Analyzes the relationships between multiple variables for prediction purposes.