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How many different simple random sample of size 7 can be obtained from a population which is a size 100?
There are 16,007,560,800 or just over 16 billion samples.
How many different simple random samples of size 4 can be obtained from a population whose size is 42?
Number of samples = 42C4 = 42*41*40*39/24 = 111930
How many simple random samples of size 5 can be selected from a population of size 35?
There are 324,632 possible samples.
How many simple random samples of size 5 can be obtained from a population whose size is 38?
You wouldn't want to use the same item twice, so just divide 38/5 = 7+ ... you can get 7 samples of size 5.
What is the definition of simple random sample?
There are two equivalent ways of defining a simple random sample from a larger population. One definition is that every member of the population has the same probability of being included in the sample. The second is that, if you generate all possible samples of the given size from the population, then each such sample has the same probability of being selected for use.
How many different simple random sample of size 7 can be obtained from a population which is a size 100?
There are 16,007,560,800 or just over 16 billion samples.
How many different simple random samples of size 4 can be obtained from a population whose size is 42?
Number of samples = 42C4 = 42*41*40*39/24 = 111930
How many simple random samples of size 5 can be selected from a population of size 35?
There are 324,632 possible samples.
How many simple random samples of size 5 can be obtained from a population whose size is 38?
You wouldn't want to use the same item twice, so just divide 38/5 = 7+ ... you can get 7 samples of size 5.
How many simple random samples are possible of size 40 from a population of size 500?
Approximately 1.364*1060
What is the definition of simple random sample?
There are two equivalent ways of defining a simple random sample from a larger population. One definition is that every member of the population has the same probability of being included in the sample. The second is that, if you generate all possible samples of the given size from the population, then each such sample has the same probability of being selected for use.
What is the formula for simple random sampling?
The formula for simple random sampling is: n = N * (X / M) Where: n = number of samples N = population size X = sample size chosen M = total number of units in the population
What is stratified random sampling in statistics?
Stratified Random Sampling: obtained by separating the population into mutually exclusive (only belong to one set) sets, or stratas, and then drawing simple random samples (a sample selected in a way that every possible sample with the same number of observation is equally likely to be chosen) from each stratum.
How can data be collected if independent samples are to be obtained?
Data can be collected for independent samples by randomly selecting individual units or cases from the population of interest. This can be done using random sampling techniques such as simple random sampling, stratified sampling, or cluster sampling. By ensuring that each sample is selected independently of the others, we can maintain the assumption of independence among the samples in the data analysis.
How many simple random samples of size 3 can be selected from a population of size 7?
7*6*5/(3*2*1) = 35
Describe how more complex probability sampling techniques could provide samples more representative of a target population than simple random sampling Illustrate your answer with a criminal justice e?
Describe how more complex probability sampling techniques could provide samples more representative of a target population than simple random sampling Illustrate your answer with an information technology example.
What is the difference between a simple random sample and a stratified random sample?
Sometimes a population consists of a number of subsets (strata) such that members within any particular strata are alike while difference between strata are more than simply random variations. In such a case, the population can be split up into strata. Then a stratified random sample consists of simple random samples, with the same sampling proportion, taken within each stratum.
