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The method of summarizing the large amounts of data by forming the frequency distributions, scatter diagrams, histograms, etc., and calculating statistics like means variances and correlation coefficients. The term is also used when obtaining the low-dimensional representation of multivariate data by methods such as principal components analysis and the factor analysis.
The procedure in which the prior distribution is required in the application of Bayesian inference, it is determined from empirical evidence, namely same data for which the posteri
data modelling
Cluster sampling : A method or technique of sampling in which the members of the population are arranged in groups (called as 'clusters'). A number of clusters are selected at the
1.Sam Lucarelli, owner of Lucarelli Products, is evaluating whether to produce a new product line. After thinking through the production process and the costs of raw materials and
Classification and regression tree technique (CART): The alternative to the multiple regression and associated techniques or methods for determining subsets of the explanatory va
Huffman code is used to compress data file, where the data is represented as a sequence of characters. Huffman's greedy algorithm uses a table giving how often each character occur
Tree is the term from the branch of the mathematics which known as the graph theory, used to describe any set of the straight-line segments joining the pairs of points in some pro
Log-linear models is the models for count data in which the logarithm of expected value of a count variable is modelled as the linear function of parameters; the latter represent
Principal components regression analysis is a process often taken in use to overcome the problem of multicollinearity in the regression, when simply deleting a number of the expla
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
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