Population vs Sample Statistics Example 2
Follow the full solution, then compare it with the other examples linked below.
Example 2
mediumDistinguish between a parameter and a statistic. Give an example of each.
Solution
- 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, ).
- 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, ).
- 3 Step 3: Parameters are usually unknown; statistics are calculated from data and used to make inferences about parameters.
Answer
Parameter: population measure (). Statistic: sample measure ().
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 โMore Population vs Sample Examples
Example 1 easy
A researcher wants to know the average height of all 16-year-olds in the UK. She measures 500 random
Example 3 easyA factory produces 10,000 light bulbs per day. Quality control tests 100 randomly chosen bulbs. Iden
Example 4 easyA website wants to know the average time spent on the site by all visitors. It studies 1,200 randoml