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These techniques are applied when the rows and the columns of the data table represent the same units and when the measure is a disiance or a similarity. The goal of the analysis is to represent graphically these distances or similarities. Multidimensional Scaling (MDS) is used to represent the units as points on a map such thbt their Euclidean distances on the map approximate the original similarities- (classic MDS, which is equivalent to PCA, is used for distances, nnnmetric MDS for similarities)'. Additive tree analysis and cluster analysis free used to reprcsent the units as "leaves" of a tree with the distance on the tree" approximating the original distance or similarity.
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
Geometric Mean The geometric mean of numbers is defined as the th root of the product of numbers .It is obtained by multiplying all the values of a variable and then extracti
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Analysis of covariance (ANCOVA) It is initially used for an expansion of the analysis of variance which permits to the possible effects of continuous concomitant variables (suc
Simple Linear Regression One calculate of the risk or volatility of an individual stock is the standard deviation of the total return (capital appreciation plus dividends) over
The median, as the name suggests, is the middle value of a series arranged in any of the orders of magnitude i.e. ascending or descending order. As distinct from the arithmetic
Simulation When decisions are to be taken under conditions of uncertainty, simulation can be used. Simulation as a quantitative method requires the setting up of a mathematical
"index number is an economic barometer" comment on this statement
How to a calculate the combined standard deviation for five groups (samples)?
A.The coupon rate of Erie-Chicago Rail is 7%. The interest rate of Florida municipal bond with equal risk is 6%. At what tax rate the two bonds are as good as each other B.Supp
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