Population vs Sample Statistics Example 2

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Example 2

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Distinguish between a parameter and a statistic. Give an example of each.

Solution

  1. 1
    Step 1: A parameter is a numerical measure describing a characteristic of the entire population (e.g., the true mean height of all UK adults, ฮผ\mu).
  2. 2
    Step 2: A statistic is a numerical measure from a sample used to estimate the parameter (e.g., the mean height of 200 surveyed adults, xห‰\bar{x}).
  3. 3
    Step 3: Parameters are usually unknown; statistics are calculated from data and used to make inferences about parameters.

Answer

Parameter: population measure (ฮผ\mu). Statistic: sample measure (xห‰\bar{x}).
The distinction between parameters and statistics is fundamental to inferential statistics. We use sample statistics to estimate unknown population parameters.

About Population vs Sample

In statistics, the population is the entire group of individuals or items you want to study, while the sample is the smaller subset you actually collect data from. We use sample statistics to estimate unknown population parameters.

Learn more about Population vs Sample โ†’

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