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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.
Linear Programming
(a) The Horton's initial infiltration capacity for a catchment is 204 mm/h and the constant infiltration value at saturation is 60 mm/h. For a rainfall in excess of 204 mm/h mainta
1) Suppose you want to test a hypothesis that two treatments, A and B, are equivalent against the alternative that the response for A tend to be larger than those of B. You plan to
You are given the differential equation dy/dx = y' = f(x, y) with initial condition y(0 ) 1 = . The following numerical method is also given: where f n = f( x n , y n )
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
There exists an unclassified data set with hidden data structures in it. The task in this assignment is to perform comprehensive Cluster Analysis in order to reveal the structures
A researcher is interested in comparing the effectiveness of three different parts of therapy for anger problems. 8 participants are randomly assigned to 3 treatment conditions: Co
A file on DocDepot in the assignments folder on doc-depot called bmi.mtp contains data on the Body Mass Index (BMI) of a population of Ottawa residents. The first column identifies
A marketing research firm was engaged by an automobile manufacturer to conduct a pilot study to examine the feasibility of using logistic regression for ascertaining the likelihood
Perform clustering of the unlabeled data set. You could use provided initial centroids set or generate your own. Also there could be considered next stopping criteria : - maxim
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