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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.
In an agricultural experiment, we wish to compare the yields of three different varieties of wheat. Call these varieties A, B and C. We have a ?eld that has been marked into a 3 *
Ten balls are put in 6 slots at random.Then expected total number of balls in the two extreme slots
Case Problem: A Bipartisan Agenda for Change In a study conducted by Zogby International, more than 700 New Yorkers were polled to determine whether the New York state government w
Simple Random Sampling In Simple Random Sampling each possible sample has an equal chance of being selected. Further, each item in the entire population also has an equal chan
Example of discrete random variable: 1. What is a discrete random variable? Give three examples from the field of business. 2. Of 1000 items produced in a day at XYZ Manufa
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Statistical Definition of probability: Ques: (a) (i) Distinguish Statistical Definition of probability from the Classical Definition. (ii) State the A
This question has two parts with multiple items to answer. You are a psychologist who has collected the subjective well-being scores of a number of elderly people aged 90 or abo
The Elementary Teachers' Federation of Ontario make the following claim on their website as of February 13, 2013: For years, the Elementary Teachers' Federation of Ontario (ETFO
how to find mse from ssr table not the anova table
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