What Is Factor Analysis?
Factor analysis is a statistical technique that studies the extraction of common factors from variable groups. First proposed by British psychologist CE Spearman. He found that there is a certain correlation between the results of students in various subjects. Students with good results in one subject often have better results in other subjects, so he infers whether there are some potential common factors, or some general intellectual conditions Affects students' academic performance. Factor analysis finds hidden, representative factors among many variables. Grouping variables of the same nature into a factor can reduce the number of variables and test hypotheses about the relationship between variables.
- The main purpose of factor analysis is to describe some of the more basic latent variables (latent factors) hidden in a set of measured variables that cannot be directly measured. For example, if you want to measure student motivation, active participation in the classroom, homework completion, and extra-curricular reading time can be used to reflect motivation. And academic performance can be reflected by mid-term and final grades. Here, learning enthusiasm and academic performance cannot be directly measured by a measure (such as a question). They must be measured by a set of measures and then combined with the measurement results in order to be more accurately grasped. In other words, these variables cannot be measured directly. What can be measured directly is just a manifestation that it reflects, or it is part of it. Here, representation and part are two different concepts. Representation is directly determined by this recessive variable. Recessive variables are the cause, and representation is the effect. For example, learning motivation is a major determinant of the degree of classroom participation (representation measure).
- Factor analysis is a powerful tool for social research, but it cannot be said with certainty that a study contains several factors. When the variables selected in the study change, the number of factors also changes. In addition, the actual meaning of each factor is not absolute.
- There are two types of factor analysis methods. One is
- Exploring factor analysis has some limitations. First, it assumes that all factors (after rotation) affect the measure. In actual research, we often assume that there is no causality between one factor, so it may not affect the measure of another factor. Second, exploratory factor analysis assumes measures
- The strength of confirmatory factor analysis is that it allows researchers to explicitly describe a
- In market research, researchers are concerned about the integration or combination of some research indicators. These concepts are usually measured through the question of grade scoring, such as variables obtained using Likert scales. The set of each indicator (or a set of related indicators) is a factor, and the index concept score is the factor score.
- Factor analysis has a wide range of applications in market research, including:
- (1) Research on Consumer Habits and Attitudes (U & A)
- (2) Research on brand image and characteristics
- (3) Investigation of service quality
- (4) Personality test
- (5) Image survey
- (6) Market division identification
- (7) Classification of customers, products and behaviors
- In practical applications, the importance scores of different factors can be derived through factor scores, and managers can decide the market problem or product problem to be solved first according to the importance of these indicators.
- The task of factor analysis is to take the correlation matrix of X and