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Sampling Distributions
The procedure of selecting the desired portion from population which describes the characteristics of whole population is
sampling
extracting
deviation of sample
variability of sample
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Sampling Distributions
The difference between corresponding population and unbiased estimate in the terms of absolute value is classified as
sampling error
random sample error
under coverage error
coverage error
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Sampling Distributions
The type of sampling in which the desired and useful information is gathered from the best position holder is classified as
quota sampling
convenience sampling
purposive sampling
judgment sampling
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Sampling Distributions
In systematic sampling, the population is 200 and the selected sample size is 50 then the sampling interval is
250
0.25
4
40
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Sampling Distributions
In sampling, the measures such as variance, mean, standard deviation are considered as
absolute statistics
coverage estimator
parameters
estimators
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Sampling Distributions
The sample statistics are denoted by the
upper case Greek letter
associated roman alphabets
roman letters
lower case Greek letter
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Sampling Distributions
The type of sampling In which each element of population has equally likely chance of occurrence in a random sample is classified as
regular and irregular sampling
error free sampling
inertia sampling
simple random sampling
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Sampling Distributions
The parameters of population are denoted by the
roman letters
lower case Greek letter
upper case Greek letter
associated roman alphabets
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Sampling Distributions
The important principles to determine the valid statistical inference must includes
principle of sampling error
principle of statistical regularity
principle of inertia
both b and c
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Sampling Distributions
The measures in sampling that are results of sample analyses are called
absolute statistics parameter
coverage estimators
population statistics
sample statistic
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