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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.
Canonical correlation analysis (CC) allows the investigation of the relationship between two ,sets of variables. For example, a sociologist may want to investigate the Relationship
Lifts usually have signs indicating their maximum capacity. Consider a sign in a lift that reads "maximum capacity 1400kg or 20 persons". Suppose that the weights of lift-users are
limitations of time series analysis
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
Agreement The degree to which different observers, raters or diagnostic the tests agree on the binary classification. Measures of agreement like that of the kappa coefficient qu
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Assume that the normal distribution applies and find the critical z value(s). A = 0.04; H1 is mean ≠ 98.6 degrees Fahrenheit. Dteremine the value of Z. Find the value of the
Let X, Y, and Z refer to the three random variables. It is known that Var(X) = 4, Var(Y) = 9, and Var(Z) = 16. It is further known that E(X) = 1, E(Y) = 2, and E(Z) = 4. Furthermor
Evaluate Gross Reproduction Rate: From the data given below compute : i) General Fertility Rate ii) Specific Fertility Rate iii) Total Fertility Rate iv)
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