In sampling errors we take a number of samples of the given mode. The samples are the models on which an analyst is working to find the errors from the number of terms which are under examination. We use the numbers of samples and then find the mean to reduce the sampling errors of the data model. In this way we define sampling errors.
For example, population of the state (increasing or decreasing); now if we want the mean height of 5th standard youngsters then we measure all the heights of sample of 5th graders in the state.
The best parameter to estimate the population is sample mean. But, there is difference between the mean sample or observed sample and the true population mean. So that, the sampling method is good or bad, if the rate of sampling is bad then likely should be some errors occur in the sample static.
The sampling errors are not easy to reduce. For example, any state wants to contact people to know how many people are homeless, the number of senior citizens, etc. The state government wants to find the parameter information but this is not easy. Then there is an error due to imperfect data collection. To reduce the sampling errors we take a number of samples of the model and then find the mean value of these samples. There are some other errors like non sampling, standard error. (know more about icse syllabus 2013, here)
The non sampling error is caused by human error by which a statistical analysis is done. These errors are not limited and not eliminated. Standard error helps us to measure the sample accuracy of the sample model. The representative sample is an unbiased indication of the data model. This is the sampling errors for grade VI. In the next session we will discuss about Selecting a sample.
For example, population of the state (increasing or decreasing); now if we want the mean height of 5th standard youngsters then we measure all the heights of sample of 5th graders in the state.
The best parameter to estimate the population is sample mean. But, there is difference between the mean sample or observed sample and the true population mean. So that, the sampling method is good or bad, if the rate of sampling is bad then likely should be some errors occur in the sample static.
The sampling errors are not easy to reduce. For example, any state wants to contact people to know how many people are homeless, the number of senior citizens, etc. The state government wants to find the parameter information but this is not easy. Then there is an error due to imperfect data collection. To reduce the sampling errors we take a number of samples of the model and then find the mean value of these samples. There are some other errors like non sampling, standard error. (know more about icse syllabus 2013, here)
The non sampling error is caused by human error by which a statistical analysis is done. These errors are not limited and not eliminated. Standard error helps us to measure the sample accuracy of the sample model. The representative sample is an unbiased indication of the data model. This is the sampling errors for grade VI. In the next session we will discuss about Selecting a sample.
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