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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 associations between the pairs of variables and higher order interactions among more than two variables.
The estimated expected frequencies under the particular models can be found from the iterative proportional fitting. Such type of models is, essentially, the equivalent for the frequency data, of the models for the continuous data used in the analysis of variance, except that interest usually now centres on parameters representing interactions rather than those for the main effects.
Profile plots is a technique of representing the multivariate data graphically. Each of the observation is represented by a diagram comprising of a sequence of equispaced vertical
The approach of controlling the error rate in an exploratory analysis where number of hypotheses are tested, but where the strict control which is provided by multiple comparison p
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Correlation matrix : A square, symmetric matrix with the rows and columns corresponding to the variables, in which the non diagonal elements are correlations between the pairs of t
How large would the sample need to be if we are to pick a 95% confidence level sample: (i) From a population of 70; (ii) From a population of 450; (iii) From a population of 1000;
Barrett and Marshall Model for conception : A biologically reasonable model for the probability of conception in a particular menstrual cycle, which supposes that the batches of sp
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Method of moments is the procedure for estimating the parameters in a model by equating sample moments to the population values. A famous early instance of the use of the proced
The scatter plots of SRES1, RESI1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plots sho
Maximum likelihood estimation is an estimation procedure involving maximization of the likelihood or the log-likelihood with respect to the parameters. Such type of estimators is
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