Contents
What does the first principal component represent?
The first principal component (PC1) is the line that best accounts for the shape of the point swarm. It represents the maximum variance direction in the data. Each observation (yellow dot) may be projected onto this line in order to get a coordinate value along the PC-line. This value is known as a score.
What does PC1 stand for?
PC1
| Acronym | Definition |
|---|---|
| PC1 | Principal Component 1 (remote sensing) |
| PC1 | Proprotein Convertase 1 (enzyme) |
| PC1 | Prohormone Convertases 1 |
| PC1 | Positive Control 1 |
How are the principal components of a variable interpreted?
In the variable statement we include the first three principal components, “prin1, prin2, and prin3”, in addition to all nine of the original variables. We use the correlations between the principal components and the original variables to interpret these principal components. Because of standardization, all principal components will have mean 0.
When to standardize variables in principal components analysis?
If the variables have different units of measurement, (i.e., pounds, feet, gallons, etc), or if we wish each variable to receive equal weight in the analysis, then the variables should be standardized before conducting a principal components analysis. To standardize a variable, subtract the mean and divide by the standard deviation:
How to analyze principal components and exploratory factor?
First go to Analyze – Dimension Reduction – Factor. Move all the observed variables over the Variables: box to be analyze. Under Extraction – Method, pick Principal components and make sure to Analyze the Correlation matrix. We also request the Unrotated factor solution and the Scree plot.
Is there a correlation between the principal components?
The correlations between the principal components and the original variables are copied into the following table for the Places Rated Example. You will also note that if you look at the principal components themselves, then there is zero correlation between the components. Principal Component