factor analysis
showing the connection of values by analyzing factors (Statistics) | ||||
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Factor Analysis definition was found in categories: Business & Finance(3) Language, Idioms & Slang(1) Science & Technology(1) Encyclopedia(1)
Factor Analysis Definition from Business & Finance Dictionaries & Glossaries
| Campbell R. Harvey's Hypertextual Finance Glossary |
Factor analysis
A statistical procedure that seeks to explain a certain phenomenon, such as the return on a common stock, in terms of the behavior of a set of predictive factors.
A statistical procedure that seeks to explain a certain phenomenon, such as the return on a common stock, in terms of the behavior of a set of predictive factors.
| MONASH Marketing Dictionary |
Factor Analysis
a statistical procedure for trying to discover the basic factors that may underlie and account for the correlations among a larger number of variables. For example, factor analysis might be used to determine and interpret the basic factors underlying some negative attitudes towards the purchase and use of male toiletries and cosmetics.
a statistical procedure for trying to discover the basic factors that may underlie and account for the correlations among a larger number of variables. For example, factor analysis might be used to determine and interpret the basic factors underlying some negative attitudes towards the purchase and use of male toiletries and cosmetics.
| Raynet Business & Marketing Glossary |
Factor Analysis
a statistical procedure that identifies clusters of related items ('factors') on a test.
a statistical procedure that identifies clusters of related items ('factors') on a test.
Factor Analysis Definition from Language, Idioms & Slang Dictionaries & Glossaries
| WordNet 2.0 |
factor analysis
Noun
1. any of several methods for reducing correlational data to a smaller number of dimensions or factors; beginning with a correlation matrix a small number of components or factors are extracted that are regarded as the basic variable that account for the interrelations observed in the data
(hypernym) correlational analysis
(derivation) factor analyse, factor analyze
(classification) statistics
Noun
1. any of several methods for reducing correlational data to a smaller number of dimensions or factors; beginning with a correlation matrix a small number of components or factors are extracted that are regarded as the basic variable that account for the interrelations observed in the data
(hypernym) correlational analysis
(derivation) factor analyse, factor analyze
(classification) statistics
Factor Analysis Definition from Science & Technology Dictionaries & Glossaries
| Electronic Statistics Textbook |
Factor Analysis
Factor Analysis. The main applications of factor analytic techniques are: (1) to reduce the number of variables and (2) to detect structure in the relationships between variables, that is to classify variables. Therefore, factor analysis is applied as a data reduction or (exploratory) structure detection method (the term factor analysis was first introduced by Thurstone, 1931).
For example, suppose we want to measure people's satisfaction with their lives. We design a satisfaction questionnaire with various items; among other things we ask our subjects how satisfied they are with their hobbies (item 1) and how intensely they are pursuing a hobby (item 2). Most likely, the responses to the two items are highly correlated with each other. Given a high correlation between the two items, we can conclude that they are quite redundant.
One can summarize the correlation between two variables in a scatterplot . A regression line can then be fitted that represents the "best" summary of the linear relationship between the variables. If we could define a variable that would approximate the regression line in such a plot, then that variable would capture most of the "essence" of the two items. Subjects' single scores on that new factor, represented by the regression line, could then be used in future data analyses to represent that essence of the two items. In a sense we have reduced the two variables to one factor.
Factor Analysis is an exploratory method; for information in Confirmatory Factor Analysis , see the Structural Equation Modeling chapter.
For more information on Factor Analysis, see the Factor Analysis chapter.
Factor Analysis. The main applications of factor analytic techniques are: (1) to reduce the number of variables and (2) to detect structure in the relationships between variables, that is to classify variables. Therefore, factor analysis is applied as a data reduction or (exploratory) structure detection method (the term factor analysis was first introduced by Thurstone, 1931).
For example, suppose we want to measure people's satisfaction with their lives. We design a satisfaction questionnaire with various items; among other things we ask our subjects how satisfied they are with their hobbies (item 1) and how intensely they are pursuing a hobby (item 2). Most likely, the responses to the two items are highly correlated with each other. Given a high correlation between the two items, we can conclude that they are quite redundant.
One can summarize the correlation between two variables in a scatterplot . A regression line can then be fitted that represents the "best" summary of the linear relationship between the variables. If we could define a variable that would approximate the regression line in such a plot, then that variable would capture most of the "essence" of the two items. Subjects' single scores on that new factor, represented by the regression line, could then be used in future data analyses to represent that essence of the two items. In a sense we have reduced the two variables to one factor.
Factor Analysis is an exploratory method; for information in Confirmatory Factor Analysis , see the Structural Equation Modeling chapter.
For more information on Factor Analysis, see the Factor Analysis chapter.
Factor Analysis Definition from Encyclopedia Dictionaries & Glossaries
| Wikipedia English - The Free Encyclopedia |
Factor analysis
Factor analysis is a statistical data reduction technique used to explain variability among observed random variables in terms of fewer unobserved random variables called factors. The observed variables are modeled as linear combinations of the factors, plus "error" terms. Factor analysis originated in psychometrics, and is used in behavioral sciences, social sciences, marketing, product management, operations research, and other applied sciences that deal with large quantities of data.
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