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Q: How do you find sample size in statistic?
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How does sample size effect the test statistic?

The larger the sample size, the more accurate the test results.


As the sample size increases what does the expected value of M do?

You have not defined M, but I will consider it is a statistic of the sample. For an random sample, the expected value of a statistic, will be a closer approximation to the parameter value of the population as the sample size increases. In more mathematical language, the measures of dispersion (standard deviation or variance) from the calculated statistic are expected to decrease as the sample size increases.


What is the meaning of Sampling distribution of the test statistic?

Given any sample size there are many samples of that size that can be drawn from the population. In the population is N and the sample size in n, then there are NCn, but remember that the population can be infinite. A test statistic is a value that is calculated from only the observations in a sample (no unknown parameters are estimated). The value of the test statistic will change from sample to sample. The sampling distribution of a test statistic is the probability distribution function for all the values that the test statistic can take across all possible samples.


Explain how to standardize a value in statistics?

The term effect size can refer to the value of a statistic calculated from a sample of data.


A Numerical Measure from a Sample Such as a Sample Mean Is Known?

sample statistic


Is a sample a number describing some characteristic of a statistic?

No. A statistic is a number describing a characteristic of a sample.


How do you find the sample size when given the standard deviation and the mean with a sample value?

You cannot from the information provided.


What is absolute sample size?

It is the number of elements in the sample. By contrast, the relative sample size is the absolute sample size divided by the population size.


How does the sample size affect an experiment?

Sample size greatly reduces any error to randomness in a given sample. Each experiment requires a proper size of a sample. The better it is fitted to the experiment, the better is the result. For example, if you are trying to find out the study habits of students at your school of 1000 kids, a sample size of 50 would be sufficient. However, if you are trying to find out the study habits of students across the US, a sample size of at least several hundred-thousand would be required, preferably several million.


What is the description of sample?

Statistic


What is the difference between 2 sample z test statistic and 2 sample t test statistic?

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Why is standard deviation of a statistic called standard error?

The standard error is the standard deviation divided by the square root of the sample size.