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Institutional surveys are the surveys in which the primary sampling units are the institutions, for instance, hospitals. Within each of the sampled institution, a sample of the patient records is selected.
The basic purpose of the two-stage design (compared to the simple random sample) are to reduce the number of institutions which are required to be subsampled, and to ignore constructing a sampling frame of the patient records for the whole population. Stratified sampling including selecting institutions with the differing probabilities based on some institutional characteristic (like size) is typically used to reduce the variability of the estimators.
Machine learning is a term which literally means the ability of a machine to recognize patterns which have occurred repetitively and to improve its performance based on the past
The model which arises in the context of estimating the size of the closed population where individuals within the population could be identified only during some of the observatio
Negative hyper geometric distribution : In sampling without replacement from the population comprising of r elements of one kind and N - r of another, if two elements corresponding
Line-intersect sampling is a technique of unequal probability sampling for selecting the sampling units in the geographical area. A sample of lines is drawn in a study area and, w
A family of the probability distributions of the form given as here θ is the parameter and a, b, c, d are the known functions. It includes the gamma distribution, normal dis
Kolmogorov Smirnov two-sample method is a distribution free technique which tests for any difference between the two populations probability distributions. The test is relied on t
Multidimensional scaling (MDS) is a generic term for a class of techniques or methods which attempt to construct a low-dimensional geometrical representation of the proximity matr
Cluster analysis : A set of methods or techniques for constructing a sensible and informative classi?cation of an initially unclassi?ed set of data, using variable values observed
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 |t | > t = 1.96
I do have a data of real gdp for each state and from 2000 to 2010 and I also have estimated population of illigel immigrants for each state from 2000 to 2010. In my thesis I am try
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