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The variables resulting from the recoding categorical variables with more than two categories into the sequence of binary variables. Marital status, for instance, if originally labeled 1 for the married, 2 for single and 3 for divorced, widowed or separated, can be rede?ned in the terms of two variables which are given as follows
Variable 1: 1 if single, 0 otherwise;
Variable 2: 1 if the divorced, widowed or separated, 0 otherwise;
For the married person both the new variables would be zero. In common the categorical variable with k categories would be recorded in the terms of k 1 dummy variables. Such recoding is made in use before polychotomous variables are used as the explanatory variables in a regression analysis to avoid the unreasonable supposition with the original numerical codes for the categories, that is the values 1; 2; ... ; k, correspond to the interval scale. This procedure is generally known as dummy coding
K-means cluster analysis is the method of cluster analysis in which from an initial partition of observations into K clusters, each observation in turn is analysed and reassigned,
calculate absorbance value from concentration
Interior analysis is the term now and again applied to analysis carried out on the fitted model in regression problem. The basic target of such analyses is the identification of
Models for the analysis of the survival times, or the time to event, data in which it is expected that a fraction of the subjects will not experience the event of interest. In a cl
Please help with following problem: : Let’s consider the logistic regression model, which we will refer to as Model 1, given by log(pi / [1-pi]) = 0.25 + 0.32*X1 + 0.70*X2 + 0.
Non-response is the term generally used for the failure to give the relevant information being collected in the survey. Poor response can be because of the variety of causes, for
replacement problem
Greenhouse geissercorrection is the method of adjusting the degrees of freedom of the within- subject F-tests in the analysis of the variance of longitudinal data so as to allow t
Yate s' continuity correction : When the testing for independence in contingency table, a continuous probability distribution, known as chi-squared distribution, is used as the app
hello I have a dataset including both categorical & numerical variable for market segmentation.how can i cluster them via k-means in matlab? thank you
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