Factor Analysis - Statswork

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FACTOR ANALYSISThe analysis of variance is not
a mathematical theorem, but rather a convenient
method of arranging the arithmetic.- Ronald
Fisher
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Factor Analysis Capabilities

• To simultaneously manage over hundred variables.
• Compensate for random error invalidity.
• Disentangles complex inter-relationships into
  their major distinct regularities.

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Factor Analysis Through Inexpensive Its Costs,
Including

• Its mathematical complications.
• Entails diverse numerous considerations in the
  application.
• Students unable to learn it in their formal
  learning.

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Types Of Factor Analysis

• EFA (Exploratory Factor Analysis)
• EFA is the most common factor analysis method
  used in multivariate statistics to uncover the
  underlying structure of a relatively large set of
  variables.
• CFA (Common Factor Analysis)
• CFA is the second most preferred method to
  extract the common variance and put them into
  factors.

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• You can insert graphs from Google Sheets

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PCA (Principal Component Analysis)
Image Factoring
GLM (General Linear Model)

• The PCA starts by extracting maximum variance and
  puts them into the first factor.

• GLM is the foundation for several statistical
  tests like ANOVA, ANCOVA, and regression
  analysis.

• It uses the OLS Regression method to predict the
  factor method is based on the correlation matrix.

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Maximum Likelihood Method

• It also uses the correlation matrix and has the
  advantage to analyze statistical models with
  different characters on the same basis.

Factor Loading Being the correlation coefficient
for the variable, factor loading explains
variance by the variable on that particular
factor. Factor Score It is all of rows and
columns used as an index of variables for further
analysis.
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Eigen Values
Also known as characteristic roots, Eigenvalues
portray variance explained by that particular
factor out of the total variance. Rotation
method Rotation method is not affected by
Eigenvalues or the percentage of variance
extracted but it affects to make it more reliable
to understand the output.
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