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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.
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Question: The weights of 60 children born to mothers in a small rural hospital were recorded. 3.63 3.54 3.15 3.90 4.29 4.06 2.91 3.36 3.3
Regression Coefficient While analysing regression in two related series, we calculate their regression coefficients also. There are two regression coefficients like two regress
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#There were three types of food, and the researcher recorded which foods were bought. Peanut Butter Banana Hamburger 15
Agency revenues. An economic consultant was retained by a large employment agency in a metropolitan area to develop a regression model for predicting monthly agency revenues ( y ).
Ask Describe What-if Analysis
The Neatee Eatee Hamburger Joint specializes in soyabean burgers. Customers arrive according to the following inter - arrival times between 11.00 am and 2.00 pm: Interval-arriva
You will recall the function pnorm() from lectures. Using this, or otherwise, Dteremine the probability of a standard Gaussian random variable exceeding 1.3. Using table(), or
the two regrassion line will pass through the point (x,y)
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