- An important idea when starting statistics is to understand the difference between populations and samples.
- Populations consist of everything or everybody you want to measure; for example, “all women in the Bay Area between the ages of 18 and 54.” “House cats raised as pets in American households.” “The light bulbs we are manufacturing in this plant.” “Every human being on planet earth.” These are all populations. Populations have parameters. If you survey everybody in a population, this is known as a census.
- A sample consists of as random a selection of objects or persons in your population as possible (called a sampling frame).
- There are many ways to do randomization, but the most important constraint is to be as close to random as possible.
- To use the above examples, we can talk about “500 women in the Bay Area between the ages of 18 and 54.”
- “50 house cats drawn from households in San Francisco, CA.” (with which we have to assume has many of the same qualities as all of America.)
- “10 light bulbs manufactured at this plant in the last year.”
- “At least 3 people from every country in the world.”
The science of statistics is based on measuring these samples; in other words, samples have statistics.
