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What is the difference between Population and sample?
Population and SamplePopulation is the area in which you are trying to get information from. Sample is a section of your population that you are actually going to survey. It is important to have a sample that will represent your entire population in order to minimize biases. For example: You want in know how American citizens feel about the war in Iraq. Your population: The United States Your sample: 500 citizens selected randomly from each state.Since the answers all over the US would greatly vary, it is important to have everyone in the population represented in your sample. This is usually done through random sampling, which assumes no biases seeing as the subjects were selected at random.
What happens to the sample size if you increase the standard deviation?
The statistics of the population aren't supposed to depend on the sample size. If they do, that just means that at least one of the samples doesn't accurately represent the population. Maybe both.
What is a experimental sample?
An experimental sample is an experiment that is just a sample of what you are looking for.
Difference between mean and expected value?
For a population the mean and the expected value are just two names for the same thing. For a sample the mean is the same as the average and no expected value exists.
Short notes with examples to explain you discriptive statistics ii inferential statistics?
Descriptive statistics give information regarding a data set. For example, any graph, the mean, median, and mode, standard deviation, range, and variance are all descriptive statistics. Inferential statistics is using a representative sample from a population to say something about that population. For example, for presidential polls, not everyone in the country is called and asked who they plan to vote for. Whoever does the surveying picks a sample that should fairly represent the population as a whole, and just asks those people. Depending on the sample size, the surveyor can then determine how accurate the results are, and use them to generalize to the population as a whole.
What would be a good reason for testing the entire population of widgets produced at your factory instead of just a sample?
to produce a product with zero defects
What is the difference between population and sample in statistics?
A population includes all members of a defined group. A sample, on the other hand, is just a part of the population.
What is the difference between Population and sample?
Population and SamplePopulation is the area in which you are trying to get information from. Sample is a section of your population that you are actually going to survey. It is important to have a sample that will represent your entire population in order to minimize biases. For example: You want in know how American citizens feel about the war in Iraq. Your population: The United States Your sample: 500 citizens selected randomly from each state.Since the answers all over the US would greatly vary, it is important to have everyone in the population represented in your sample. This is usually done through random sampling, which assumes no biases seeing as the subjects were selected at random.
Why sample is chosen instead of testing the entire population?
Sometimes, there are too much of the thing you are testing, so it is a lot easier to just take a sample. For example, if there were twelve million weeds growing on a field and you wanted to see how many of them were dandelions, it would take forever to count all the dandelions on that field. It is more practical just to take a small sample.
Why might researchers study just a sample of a large population rather than the whole population?
Because the whole population might be too large to sample. A good example is the population of the world. At nearly 7 billion people, it would be unrealistic to sample each person to determine some factor that you are looking at. Generally, we sample a subset of the population, taking into account differences (or errors) that might result, in this case, regional and cultural, in order to estimate the behavior of the larger population.
What happens to the sample size if you increase the standard deviation?
The statistics of the population aren't supposed to depend on the sample size. If they do, that just means that at least one of the samples doesn't accurately represent the population. Maybe both.
Why inferential statistics is not required in census?
Inferential statistical methods are used when data is collected from a sample in the population. Inferential statistics are used to generalize the results of the sample to the population. In a census you have data from each and every member of the population, so you just use descriptive statistics.
What does sample to draw an inference about the population mean?
you just put the phone number in it the push dile
Difference between sample and sampling frame?
A sample is a smaller group selected from a larger population. It may be to costly and time consuming to carry out the study on the whole population so the researchers choose a sample and often generalise results.A sample frame is the list of people from which a sample for the study are selected. It is only carried out on the target population that the researcher is interested in studying. For example finding data on just school children would not involve the the whole population only children in schools.
Example population for simple radom sampling?
A population just means the set of individuals, items, or data from which a statistical sample is taken. It could be anything. All Americans, the students at a University, etc. The random sample would be the randomly selected "test" group of students, citizens, items, or data from said population.
What is a experimental sample?
An experimental sample is an experiment that is just a sample of what you are looking for.
What is data and sample?
Data is commonly referred to the quantitative attributes of a variable. A data is nothing but a result of something. Through this result, the information is derived. Sometimes we refer to Raw Data which is unprocessed in nature which can mean a collection of numbers or characters that collect information and then convert from quantities to symbols. Sample, in statistics can mean a subset of a population. Population can be huge, so the sample can represent just a manageable size. Sample is first collected and then the statistics are derived from the sample. This process is known as Sampling.
