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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.
You have learned that there are 3 major central measures of any data set. Namely: mean, median, and mode. Which of the three, do the outliers affect the most?
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
Coefficient of concordance : The coef?cient is taken in use to assess the agreement among m raters ranking n individuals according to some of the speci?c characteristic. Which can
Independent component analysis (ICA) is the technique for analyzing the complex measured quantities thought to be mixtures of other more fundamental quantities, into their fundamen
regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual
Hazard function : The risk which an individual experiences an event in a small time interval, given that the individual has survived up to the starting of the interval. It is th
Matching is the method of making a study group and a comparison group comparable with respect to the extraneous factors. Generally used in the retrospective studies when selecting
The values assigned to factors for the individual sample units in a factor analysis. The most common approach is "regression method". When the factors are seen as the random variab
Oracle property is a name given to techniques for estimating the regression parameters in the models fitted to high-dimensional data which have the property that they can correctl
Multilevel models are the regression models for the multilevel or clustered data where units i are nested in the clusters j, for example a cross-sectional study where students are
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