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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.
what are characteristics of a population for which it would be appropiate to use mean/median/mode
Sequential Sampling Under this method, a number of sample lots are drawn one after another from a universe depending on the results of the earlier samples. Such sampling is gen
To study the physical fitness of a sample of 28 people, the data below was collected representing the number of sit-ups that a person could do in one minute. 10 12
In a study of outcomes for patients who had been in the Intensive care Unit (ICU) at a large hospital, the records from last 150 patients who had been in the ICU for more than one
Caveat We must be careful when interpreting the meaning of association. Although two variables may be associated, this association does not imply that variation in the independ
Statistical Process Control The variability present in manufacturing process can either be eliminated completely or minimized to the extent possible. Eliminating the variabilit
difference between large sample test and small sample test
The PCA is amongst the oldest of the multivariate statistical methods of data reduction. It is a technique for simplifying a dataset, by reducing multidimensional datasets to lower
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i m doing MBA in singapore and i want a good work. i want a data for 200 observations and then answers for some questions. and i need the data to be approved by our professor first
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