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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
Product-limit estimator is a method for estimating the survival functions for the set of survival times, some of which might be censored observations. The logic behind the procedu
Categorizing continuous variables : A practice which involves the conversion of the continuous variables into the series of the categories, which is common in the field of medical
what is measures of variability?
Cause specific death rate : A death rate calculated for the people dying from the specific disease. For instance, the below given are the rates per 1000 people for three disease cl
the problem that demonstrates inference from two dependent samples uses hypothetical data from TB vaccinations and the number of new cases before and after vaccinations for cases o
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
A test for equality of the variances of the two populations having normal distributions, based on the ratio of the variances of the sample of observations taken from each. Most fre
Law of likelihood : Within framework of the statistical model, a particular set of data supports one statistical hypothesis or assumption better than another if the likelihood of t
The nonparametric Bayesian inference approach to using the finite mixture distributions for modelling data suspected of the containing distinct groups of observations; this approac
The Null Hypothesis - H0: β 1 = 0 i.e. there is homoscedasticity errors and no heteroscedasticity exists The Alternative Hypothesis - H1: β 1 ≠ 0 i.e. there is no homoscedasti
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