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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
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The functions of the data and the parameters of interest which can be brought in use to conduct inference about the parameters when full distribution of the observations is unknown
Outlier is an observation which seems to deviate markedly from the other members of the sample in which it happens. In the set of systolic blood pressures, {125, 128, 130, 131, 19
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
Chi-squared distribution : It is the probability distribution, f (x), of the random variable de?ned as the sum of squares of the number (v) of independent standard normal variables
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The term used in a variety of methods in statistics, but mostly to refer to the categorical variable, with a less number of levels, under examination in an experiment as a possible
The Null Hypothesis - H0: There is no heteroscedasticity i.e. β 1 = 0 The Alternative Hypothesis - H1: There is heteroscedasticity i.e. β 1 0 Reject H0 if Q = ESS/2 >
Write a c++ program to find the sum of 0.123 ? 103 and 0.456 ? 102 and write the result in three significant digits
Normality - Reasons for Screening Data Prior to analyzing multivariate normality, one should consider univariate normality Histogram, Normal Q-Qplot (values on x axis
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