Sampling Distributions

Sampling Distributions
In statistical analysis, the sample size is considered large if
n > or = 30
n < or = 30
n > or = 50
n < or = 50
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Sampling Distributions
In sample distribution, the degree of freedom is calculated as
df = n- 2
df = n- 1
df = n- 3
df = n- 5
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Sampling Distributions
The method of sampling in which the random sampling will not be possible because the population is widely spread is classified as
secondary stage sampling
multistage sampling
primary stage sampling
sub stage sampling
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Sampling Distributions
The distribution which consists of all the values of sample statistic of sampling is classified as
statistic distribution
sampling distribution
possibility distribution
valuable distribution
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Sampling Distributions
The bias in which few respondents responds to offered questionnaire is classified as
responsive bias
non-responsive bias
distributed error
concerning error
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Sampling Distributions
In the systematic sampling, the value of k is classified as
sampling interval
sub stage interval
secondary stage interval
multistage interval
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Sampling Distributions
The cluster sampling, stratified sampling and systematic sampling are types of
direct sampling
indirect sampling
random sampling
non random sampling
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Sampling Distributions
If the standard deviation of the population is 35 and the sample size is 9 then the standard deviation of sampling distribution is
12.67
11.67
13.67
14.67
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Sampling Distributions
All the values in sample distribution that can freely varies in the selected random sample from population are indicated as
degree of freedom
degree of error
degree of statistic
degree of possibility
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Sampling Distributions
The bias which occurs when the randomly drawn sample from population fails to represent whole population is classified as
populated bias
random sample bias
under coverage bias
coverage bias
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