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Sampling Distributions
The method of random sampling which is also called area sampling method is classified as
statistical sub cluster sampling
sub cluster sampling
proportional inertia sampling
cluster sampling
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Sampling Distributions
In stratified sampling, the sample drawn randomly from the strata is classified as
sub strata
sub sample
direct sub group
indirect sub group
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rikazzz
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Sampling Distributions
If the standard deviation of the population is known then the μ must be equal to
absolute value of estimator
error free mean
expected value of mean
inferential value of mean
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rikazzz
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Sampling Distributions
If the value of x-bar is 70 and the μ of sampling distribution is 15 with the standard deviation is 20 then the standard normal variable is
2.75
3.75
4.75
5.75
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rikazzz
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Sampling Distributions
The theorem which states that as the sample size increases the sampling distribution must approach the normal distribution is classified as
limited approximation theorem
secondary limit theorem
primary limit theorem
central limit theorem
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rikazzz
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Sampling Distributions
If the value of p is 0.70 and the sample size is 28 then the value of standard deviation of sample proportion is
0.097
0.067
0.087
0.077
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rikazzz
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Sampling Distributions
In sampling distribution, the formula of calculating standard deviation of sample proportion is as
square root of pqn ⁄ p
square root of pq ⁄ n
square root of nq ⁄ p
square root of pn ⁄ q
Author:
rikazzz
Comment
Sampling Distributions
In cluster sampling, the elements of selected clusters are classified as
elementary units
primary units
secondary units
proportional units
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rikazzz
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Sampling Distributions
The listing of elements in the population with the identifiable number is classified as
regularity experimental frame
indirect experiment frame
direct experimental frame
frame for experiment
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rikazzz
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Sampling Distributions
If the population parameter μ and the unbiased estimate of population is x̅ then the sampling error is as
|p‾ – μ|
|x̅ – μ|
|x̅ + μ|
|x̅ * μ|
Author:
rikazzz
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