Factor Analysis is a statistical method used to reduce the number of variables in a dataset. It does so by finding relationships between the original variables and grouping them into factors. These factors are then used as the new variables, which represent the data in a more concise manner.
Factor Analysis can be used in a variety of ways. It can help identify underlying patterns in data, and can be used to create more accurate predictive models. It can also be used to analyze customer surveys and other qualitative data, as it can identify the most important factors that influence customer satisfaction.
Overall, Factor Analysis can be a useful tool for those looking to make sense of large, complex datasets. It can help reduce the complexity of the data and make it easier to analyze and interpret. For those looking to gain insight from their data, Factor Analysis is a powerful tool to have in their arsenal.
StatLog 
Leave a comment