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This is a very vague area for new students in Statistics, especially for non-math students.
Random Sample: Each member of the entire population has an equal chance of being selected.
Simple Random Sample: You can select groups of size n from the entire population, and every possible group has the same chance of being selected.
Example: Consider a box with 100 marbles.
Random Sample: Reach in and select one marble. Each marble has the same chance of being selected.
Simple Random Sample: Reach in and select marbles in groups of 6 (n = 6). No matter how many times you do this, every possible group of six marbles has the same chance of being selected. If you then try selecting groups of 17 (n = 17) marbles, you will also find that every possible group of 17 marbles has an equal chance of being selected.
Random, but not Simple Random: For the Presidential Election, lets say you select a random sample of all voting precincts in your state, then interview *all the voters as they leave the polling place. The sample is random because all precincts have an equal chance of being selected. The sample is not simple random, because those voters from precincts that were *not* selected have no chance of being interviewed. This is also known as a Cluster Sample.
There is no such thing as a sample that is "Simple Random, but not Random" because n can also equal a sample of size 1.
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What is the difference between simple random sampling and random sampling?
Simple!
what is needed for simple random sample?
A reason for requiring a sample.
How can you determine whether a sample is representative of a population?
Take a simple random sample.
When you draw a sample from a normal distribution what can you conclude about the sample distribution?
The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.
What is the difference between stratified an random sampling?
In (Simple) random sampling, all of the units in the sample have the same chance of being included in the sample. Units are selected randomly from a population by some random method that gives equal probability to each element. In stratified random sampling, the entire population is divided into heterogeneous sub-popuation known as strata (sub-population with unequal variances) and a random sample is chosen from each of these stratum. The reason when to use which depends on the situation and need of the experimenter.
What is the difference between simple random sampling and systematic random sampling?
simple random sample is to select the sample in random method but systematic random sample is to select the sample in particular sequence (ie 1st 11th 21st 31st etc.)• Simple random sample requires that each individual is separately selected but systematic random sample does not selected separately.• In simple random sampling, for each k, each sample of size k has equal probability of being selected as a sample but it is not so in systematic random sampling.
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.
What is the difference between simple random sampling and random sampling?
Simple!
what is needed for simple random sample?
A reason for requiring a sample.
How can you determine whether a sample is representative of a population?
Take a simple random sample.
What does SRS mean in statistics?
Simple Random Sample
When you draw a sample from a normal distribution what can you conclude about the sample distribution?
The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.The answer depends on how the sample is selected. If it is a simple random sample, of size n, then it is distributed approximately normally with the same mean as the population mean.
What is the difference between stratified an random sampling?
In (Simple) random sampling, all of the units in the sample have the same chance of being included in the sample. Units are selected randomly from a population by some random method that gives equal probability to each element. In stratified random sampling, the entire population is divided into heterogeneous sub-popuation known as strata (sub-population with unequal variances) and a random sample is chosen from each of these stratum. The reason when to use which depends on the situation and need of the experimenter.
How do sampling methods effect the rigor of a study?
A sample needs to be random and if not a simple random sample of the whole population then a stratified random sample (there are different ways to stratify). Otherwise the study is a waste of time.
A way to collect survey data?
A simple random sample is good!
When dividing a population into subgroups so that a random sample from each subgroup can be collected?
simple random sampling
What You decide you want your sample to be representative of the population. Which sampling process would provide the most representative sample?
A simple random sample.
