Of the three purposes for regression analysis, this example focuses on describing and predicting.
General Example: If you were planning an outdoor party in the summer time, you might need to estimate how many soft drinks to buy. In your planning, you will, of course, need to know how many people will be attending. However, as you determine the number of soft drinks for each person, you might want to also consider how hot it will be. The temperatures have been forecasted for around 95 degrees on the day of the outdoor party. (In real life, you would probably make an estimate based on your previous experience and make a logical increase based on the temperature.) We will use some hypothetical data to determine how thirsty people might be. We will use the Temperature/Water example data for this.
Specific
Example: Assume that during a three-hour period spent outside, a person
recorded the temperature and their water
consumption. The experiment was
conducted on 7 randomly selected days during the summer. The data is shown
in the table below with the temperature placed in increasing order.
| Data | Corresponding |
|
| Temperature (F) | Water Consumption (ounces) |  |
75 |
16 |
|
83 |
20 |
|
|
85 |
25 |
|
85 |
27 |
|
92 |
32 |
|
97 |
48 |
|
99 |
48 |
|
We will use the Temperature/Water example to learn how to interpret the results of a simple linear regression equation and measure the strength of the association.
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