Difference in goals between pca and fa, Applied Statistics

Assignment Help:

In PCA the eigknvalues must ultimately account for all of the variance. There is no probability,'no hypothesis, no test because strictly speaking PCA is not a statistical procedure. The PCA is merely a mathematical manipulation to recast m variables as m factors. Factor analysis (FA), however, brings a priori knowledge to the problem solving exercise.

'There is a short list of primary assumptions behind factor analysis. But basically. factor analysis assumes that there are  cowelations/covariances between the m variables in the datp set that are a result of p underlying, mutually uncorrelated factors.


Related Discussions:- Difference in goals between pca and fa

Find the relation between two substance, Find the Relation between two subs...

Find the Relation between two substance: The following table shows the results obtained in experiments aimed to determine how solubility of water in benzene depends on tempera

The incidence of occupational disease , The incidence of occupational disea...

The incidence of occupational disease in an industry is such that the workers have a 20% chance of suffering from it. What is the probability that out of six workers 4 or more will

Regression coefficient, Regression Coefficient While analysing regressi...

Regression Coefficient While analysing regression in two related series, we calculate their regression coefficients also. There are two regression coefficients like two regress

Introduction to multiple regression, In simple regression the dependent var...

In simple regression the dependent variable Y was assumed to be linearly related to a single variable X. In real life, however, we often find that a dependent variable may depend o

Linear regression, Linear Regression Generally, in two mutually related...

Linear Regression Generally, in two mutually related statistical series, the regression analysis based on graphic method. Under graphic method the values  of X and Y variable

Assumptions in regression, Assumptions in Regression To understand the...

Assumptions in Regression To understand the properties underlying the regression line, let us go back to the example of model exam and main exam. Now we can find an estimate o

Admissibility, Admissibility A very common concept which is applicable ...

Admissibility A very common concept which is applicable to any procedure of the statistical inference. The underlying notion is that the procedure/method is admissible if and o

Probability, HOW WOULD YOU INTERPRET THIS PROBABILITY:P(a)=1.05

HOW WOULD YOU INTERPRET THIS PROBABILITY:P(a)=1.05

Factor loadings matrix, As we stated above, we start factor analysis with p...

As we stated above, we start factor analysis with principal component analysis, but we quickly diverge as we apply the a priori knowledge we brought to the problem. This knowled

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd