Factor analysis is a mathematical concept that is used to describe variability among observed, correlated variables. It can be defined as a data reduction technique that researchers use to investigate concepts. The concepts that cannot be measured directly are most appropriate to be measured using factor analysis. This mathematical concept is helpful to compress a large pool of data into a handful of comprehensible underlying factors. The aim of this analysis is to compile data and ensure they are easily understood by everyone.
Students can use factor analysis to solve various mathematical problems. By applying this method, researchers can spot trends and see themes throughout the data sets. As a result, researchers can see the common data points and reduce their scope of research or work.
The concept of factor analysis can be applied to various fields. However, the common objectives of this concept are:
- It helps students and researchers understand how many factors are needed to explain common themes amongst a common set of data.
- To determine if each variable in the data sheet is associated with a common theme or factor.
- To interpret the common factors available in the dataset.
- To determine the degree to which common data points are recorded in the themes or observations.
Two types of factor analysis can help students and researchers. These two types are: exploratory and confirmatory. Students need to learn about both these types of analysis to score better in exams. Moreover, these concepts can be applied to other parts of the research area.