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Post stratification adjustment: One of the most often used population weighting adjustments used in the complex surveys, in which weights for the elements in a class are multiplied by a factor so that total sum of the weights for the respondents in the class equals the population sum for the class. The technique is broadly used in household surveys to control the weighted sample totals to known population totals for particular demographic subgroups. For instance, in the US National Health Interview Survey, post stratification by sex, age, and race is employed.
Quittingill effect is a problem which occurs most frequently in studies of the smoker cessation where smokers frequently quit smoking following the onset of the disease symptoms
Kleiner Hartigan trees is a technique for displaying the multivariate data graphically as the 'trees' in which the values of the variables are coded into length of the terminal br
I need a statistics project done. How much will it cost?
The non-trivial extraction of implicit, earlier unknown and potentially useful information from data, specifically high-dimensional data, using pattern recognition, artificial inte
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
Initial data analysis (IDA): The first phase in the examination of the data set which comprises number of informal steps including the following steps * checking the quality o
Banach's match-box problem : The person carries two boxes of matches, one in his left and one in his right pocket. At first they comprise N number of matches each. When the person
Grade of membership model: This is the general distribution free method for the clustering of the multivariate data in which only categorical variables are included. The model ass
Geo statistics: The body of methods useful for understanding and modelling spatial variability in a course of interest. Central to these techniques is the idea that measurements t
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
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