Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
Multi stage or Cluster Random sampling
Under this method, the random selection is made of primary, intermediate and final units from a given population. The area of investigation is scientifically restricted to a small number of ultimate units which are representative of the whole. This will reduce the cost compared with a simple sampling from the whole area with a number of straight random selections. For example, from a population of a climatic region of the eastern states the two and south eastern from within each of these primary sampling areas a certain number of blocks May e selected are random or ultimate selection of the village for complete enumeration of households. At each stage there is a random selection and the size of sample may be proportional or disproportional depending on the size variations relevant to the purpose of inquiry.
Merits:
(1) It introduces flexibility in the sampling method which is lacking in other methods.
(2) This method is very helpful in large scale investigations where the preparation of list of all units of the universe is very difficult and expensive. For example in a socio economic survey certain families are to be selected from different village different villages are to be selected from the list of districts of a state which are given ,This is a case of three stage sampling. It will consume time and money in the selection of items from the population.
(3) This method is useful in such cases where sub division into second stage units be carried out only for such first stage units which are included in the sample.
Limitations:
A multi stage sample is usually less accurate than a sample containing the same number of final stage units selected by means of suitable multi stage process.
The Null Hypothesis - H0: β0 = 0, H0: β 1 = 0, H0: β 2 = 0, Β i = 0 The Alternative Hypothesis - H1: β0 ≠ 0, H0: β 1 ≠ 0, H0: β 2 ≠ 0, Β i ≠ 0 i =0, 1, 2, 3
The first step in this case is to ensure that you are adequately clear on the General Linear Model and its relationship to both ANOVA and regression. The distinction is approxim
For a distribution of scores with = 82 and standard deviation = 2.5, find the following: (Don't forget to sketch the normal curve to help you visualize what you are trying to fi
(1) What values can the response variable Y take in logistic regression, and hence what statistical distribution does Y follow? The response variable can take the value of either
Melissa Bakery is preparing for the coming thanksgiving festival. The bakery plans to bake and sell its favourite cookies; butter cookies, chocolate cookies and almond cookies. A k
Risk of Portfolios So far, we have seen the application of standard deviation in the context of risk in single investment. But usually most investors hold portfolios of securi
Other Measures of Dispersion In this section, we look at relatively less used measures of dispersion like fractiles, deciles, percentiles, quartiles, interquartile range and f
Related Positional Measures Besides median, there are other measures which divide a series into equal parts. Important amongst these are quartiles, deciles and percentiles.
Consider the following linear regression model: a) What does y and x 1 , x 2 , . . . . x k represent? b) What does β o , β 1 , β 2 , . . . . β k represent?
Assume that the pulley at A is a small frictionless pulley. The cord AB is only allowed to support a maximum tension in Newtons as given in P4, and the cord supporting the block ca
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd