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A population consists of all the members of a group of interest. Since it may be impractical to examine every member of a population, a sample — a subset of the population — is sometimes selected to represent the population. The sample can then be analyzed to draw conclusions about the entire population.
Let's consider our situation.
At a bridal shower, a sticker was placed at the bottom of three random plates. The guests who receive the stickered plates win a prize. |
Here, the population consists of the guests who attended the bridal shower. The sample consists of the guests who received the stickered plates. Samples can be classified into different categories.
Name | Characteristic |
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Simple Random Sample | Each member of the population has an equal chance of being selected. |
Systematic Sample | Members are selected according to a specified interval from a random starting point. |
Self-selected Sample | Members volunteer to be included in the sample. |
Convenience Sample | Members that are readily available or easy to reach are selected. |
Stratified Sample | The population is first divided into similar, nonoverlapping groups. Members are then randomly selected from each group. |
In our situation, all guests have an equal chance of receiving a stickered plate. This means that we have a simple random sample. Let's finally summarize our answers in a table.
Sample | Guests who received the stickered plates |
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Population | All guests |
Classification | Simple random sample |
Explanation | All guests had an equal chance of receiving a stickered plate |