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Lesson 1: Statistical Methods
2 Populations and Samples < Back | Next >
The act of conducting a study begins with the collection of some measurement or number commonly called a random variable.

Random variables are any measurable characteristic or trait, in other words a measurement!

Example

We could measure the diameter of a tree or the spread rate of a forest fire. The object from which we collected the data is called an experimental unit. So for the last two examples the experimental unit would be a tree and the forest fire.

Population

A population is the set of all values of a single measurement (random variable) collected under certain conditions called the environmental conditions.

example 1 EXAMPLE 2
The population is equal to the set of all diameters of all trees on the Boise National Forest in 2006. The population is equal to the fire spread rate for all forest fires on the Boise National Forest during 2006.
 

In both cases our environmental conditions limit our population to the Boise National Forest in 2006.

Sample

A sample is a subset of the population. For example, we may only measure the diameter of 20,000 trees or collect the spread rate for 10 of forest fires on the Boise National Forest in 2006.

Although we are usually interested in the population we can often not obtain measurements on the entire population. So a sample provides us with some information about the population.

Remember that both populations and samples are sets of numbers, they are never sets of physical units or experimental units.

Example

Population is equal to the set of all trees on the Boise national Forest in 2006. This statement is wrong; it should read the population is equal to the set of diameters for all trees on the Boise National Forest in 2006.

LESSON 1
1 Concepts and Terms
2 Populations and Samples
3 Parameters and Statistics
4 Descriptive Statistics
5 Inferential Statistics
6 Review Questions
< Back | Next >

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