Factor Analysis and Research Methods

A statistical technique used to simplify a set of variables by grouping them into underlying factors. The goal is to reduce the complexity of data while retaining the most important information.

A process in factor analysis where the axes representing the factors are rotated to improve the interpretability of the results. This is done by aligning the axes more closely with the data points.

A type of factor rotation where the axes are kept at right angles (90 degrees). This ensures that the factors remain independent of each other.

A situation in factor analysis where a variable loads significantly on one factor and has minimal or no loading on other factors. This indicates that the variable is strongly associated with a specific underlying construct.

A situation in factor analysis where a variable loads significantly on only one factor and not significantly on other factors. This indicates that the variable is distinct from other underlying constructs.

A statistical test that assesses the suitability of data for factor analysis. It checks if the correlations between variables are sufficiently strong to justify factor extraction.

The proportion of variance in a variable explained by all the extracted factors. A higher communality (closer to 1) indicates a stronger fit to the factor solution.

A type of factor rotation that assumes factors are uncorrelated (independent). This is widely used for simplicity and ease of interpretation.

A type of factor rotation that allows factors to be correlated. It's often preferred for complex data where factor relationships are important.

A statistical measure of internal consistency, indicating how well items on a scale measure the same underlying construct. Values closer to 1 show greater reliability, a generally accepted threshold being 0.7.

A measure of how much variation in a variable is explained by the common factors in a factor analysis model. It ranges from 0 to 1, where 1 indicates that the factor perfectly explains the variable.

A method in factor analysis that aims to explain the total variance of all variables using a set of linear combinations. It aims to find factors that capture the maximum amount of variance in the data.

In factor analysis, the loading of a variable on a factor refers to the correlation between the variable and the factor. It indicates the strength and direction of the relationship.

A variable that is manipulated or controlled by the researcher to observe its effect on the dependent variable. In an experiment, the independent variable is the treatment being applied to different groups, such as different waiting times in a customer service study.

A variable that is measured or observed in an experiment to see how it is affected by changes in the independent variable. In a customer service study, this could be a customer's perception of service quality or their purchase intention.

A statistical test used to compare the means of two or more groups. It is used to determine if there is a statistically significant difference between the groups, or if the observed differences are likely due to chance.

The category or level within a factor that represents a specific treatment condition. For example, in a waiting time experiment, 'below average waiting time' would be a level of the 'waiting time' factor.

The statement that there are no differences between the means (averages) of the groups being compared. ANOVA is used to test this assumption. If the differences are statistically significant, the null hypothesis is rejected.