spss-Variance Analysis

Variance Analysis (single-factor variance analysis, multivariate ANOVA, covariance analysis)

Basic Concept: The comparison of two or more means is performed to test the significance of the difference in the mean of two or more two samples (t test is mainly to test the significance of the difference in the mean of two samples)
basic idea: to determine the size of the influence of the control variables on the results of the study by analyzing the contribution of the variation of different variables to the total variance
precondition: The normal distribution with the same variance of the population mean under different levels

1. Single-Factor variance analysis: testing whether the different levels of a control variable cause significant differences and changes in the observed variables
Calculation: F-Test
2. Multivariate Variance Analysis: analysis of the role of multiple control variables, the interaction of multiple control variables, and whether other random variables have a significant impact on the results
Calculation: The total deviation squared sum of the observed variables is decomposed into 3 parts: the sum of squares caused by the individual action of multiple control variables; the sum of squared deviations caused by the interaction of multiple control variables; the sum of squared deviations caused by other stochastic factors
3. Covariance analysis: It is difficult to control the factors as a co-variable, in the context of the influence of the dispatch of the covariance, analysis of the influence of control variables on the observed variables
Requirements: The covariance is a continuous numerical type, and multiple co-variables are independent from each other, and there is no interaction between the control variables.

Note: control variables in single-factor and multi-factor anova are qualitative variables, while covariance analysis includes both qualitative variables (control variables) and quantitative variables (covariance)

SPSS operation

1. Single-Factor variance analysis

2. Multi-factor variance analysis and covariance analysis

spss-Variance Analysis