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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.
The cornlnunalities h j represent the fraction of the total variance' 'accounted for of variabie j. Ry calculating the communalities we can keep track of how much of-the orig
#question what is the statistical process to reduce hardness of water
Identify the (time, censor) pair for each of the following analyses:
The data used is from a statistical software Minitab; London.MPJ is the file that consists of 1519 households drawn from 1980 - 1982 British Family Expenditure Surveys. Data that i
Central Tendency and Dispersion in Statistics: Write a note on the following : i) What is the importance of Measures Of Central Tendency and Dispersion in Statistics ?
How can we analyse data with four bilateral response variables measured with errors and three covariated measured without errors?
Collect data about the chosen business problem or opportunity at the company. Explain how you obtained a suitable sample of either qualitative or quantitative data. Review data f
Question Following the general methodology used by econometricians as explained in the session for week 1 (eight steps), explain how you would proceed to determine if a good com
solve problems
Multivariate analysis of variance (MANOVA) is a technique to assess group differences across multiple metric dependent variables simultaneously, based on a set of categorical (non-
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