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Why use sample instead of population?
When performing an experiment or gathering data for statistics, it would be very difficult to gather information for every member of the group's population. Instead, one can gather information from a sample large enough to be representative of the population.
What is independent values?
sample data drawn from one population is completely unrelated to the selection of sample data from the other population.
Difference between sample regression and population regression line?
AnswerA sample is a subset of a population. Usually it is impossible to test an entire population so tests are done on a sample of that population. These samples can be selected so that they are representative of the population in which cases the sample will have weights, strata, and clusters. But usually people use random samples. So it's not that the line is different, it's that the line comes from different data. In stats we have formulas that allow a sample to represent a population, if you have the entire population (again unlikely), you wouldn't need to use this sample formulas, only the population formulas.
What is the similarities between population and sample?
Similarity: Both are counts of people/animals/things. Difference: Population is the total # of things, while sample is the # of things that you gather data on. If you pick the right sample size, you can be pretty confident that the results of the sample data is the same as the results of the entire population.
What is the definition of sample size in math?
The sample size is the number of elements, out of a population, for which some data are measured in order to make assessments about the population.
Is the data is sample or population?
Data is neither sample nor population. Data are collected for attributes. These can be for a sample or a population.
What are the main problem in data gathering?
I would imagine that it is getting a representative sample number and a fraction of the population that does not have bias to the study in question
Why use sample instead of population?
When performing an experiment or gathering data for statistics, it would be very difficult to gather information for every member of the group's population. Instead, one can gather information from a sample large enough to be representative of the population.
Why is it only possible to estimate the mean median and quartiles?
In reality, a statistician never really has ALL the data. The data is instead taken from a sample of the whole population. If this sample is representative of the entire population, then any statistics based on the sample should be good estimates of the whole but probably not a perfect match. Of course the more data you get from the whole population the better the estimate, but it will always be an estimate unless you census the enitire population.
Why does the possibility of sampling error present a problem to researchers when inferring a population from a sample?
The data will most likely not be representative of the population as a whole and therefore be unreliable, and have the researchers making bad conclusions
What is an independent value?
sample data drawn from one population is completely unrelated to the selection of sample data from the other population.
What is independent values?
sample data drawn from one population is completely unrelated to the selection of sample data from the other population.
How can you tell if the population data is related to the sample data?
There are Goodness-of-Fit tests that can be used. The choice of test will depend on what is known about the population and sample data.
The most important step to ensure accuracy in a sample is?
The most important step to ensure accuracy in a sample is random selection. By randomly choosing samples from the population, you minimize bias and increase the likelihood that your sample is representative of the entire population. This helps to draw reliable conclusions and make valid inferences based on the sample data.
Difference between sample regression and population regression line?
AnswerA sample is a subset of a population. Usually it is impossible to test an entire population so tests are done on a sample of that population. These samples can be selected so that they are representative of the population in which cases the sample will have weights, strata, and clusters. But usually people use random samples. So it's not that the line is different, it's that the line comes from different data. In stats we have formulas that allow a sample to represent a population, if you have the entire population (again unlikely), you wouldn't need to use this sample formulas, only the population formulas.
When using data from population genetics research the sample must be?
The sample must have a high probability of representing the population.
What type of research technique does a sociologist ensure that data are statistically representative of the population being studied?
A sociologist can ensure that their data are statistically representative of the population being studied by using random sampling techniques. This involves selecting a sample of participants from the population in a way that gives each member an equal chance of being chosen. By using random sampling, sociologists can generalize their findings to the larger population with more confidence.
