Sampling distribution

What Sampling distribution is

Sampling distribution is the probability distribution of a statistic obtained by taking repeated samples of the same size from a given population. It describes how the sample statistic is likely to vary from sample to sample.

Steps for Sampling distribution:

  1. Select a population of interest.

  2. Define the sample statistic of interest.

  3. Select a sample size.

  4. Take repeated samples of the same size from the population of interest.

  5. Calculate the sample statistic for each sample.

  6. Plot the sample statistics in a histogram or a frequency distribution. This is the sampling distribution.

  7. Examine the sampling distribution to make inferences about the population parameters.

Examples

  1. Estimating a population mean: Sampling distributions can be used to estimate population means by taking a random sample of a population and calculating the mean of the sample.

  2. Estimating a population proportion: Sampling distributions can be used to estimate population proportions by taking a random sample of a population and calculating the proportion of individuals in the sample with a particular characteristic.

  3. Testing a hypothesis: Sampling distributions can be used to test a hypothesis by taking a random sample of a population and using the sample data to test the hypothesis.

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