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Graphing Tips and Examples:
Graphing Information
- This exercise lends itself well to graphing. Graphing allows scientists to see relationships between numbers. In order to graph something, all you need is:
- data to graph
- a spreadsheet program or graph paper
In this lesson, the variables to graph include Ozone, Temperature, and, Wind
Speed.
There are many types of charts and
graphs. Some are easier to understand than others, but the reason for different types
of graphs is that each type has a fairly specific use. For the
data analysis portion of the activities, students will utilize bar graphs.
- Bar Graph
Bar graphs are used to show how a variable changes over time or to compare items. Bar graphs have an x-axis (horizontal) and a y-axis (vertical). Typically, the x-axis has
numbers representing the time period, and the y-axis represents the amount of
the variable being measured, in this case, ozone, temperature, cloud cover,
and wind speed.
There are many useful characteristics of bar graphs,
including; making comparisons between different variables very easy to see; and bar
graphs clearly show trends in data, meaning that they show how one variable
can change as the other increases or decreases.
Students may create graphs by hand, or by using a spreadsheet program.
The following is an example of how graphs would be created and appear if a
spreadsheet program was utilized.
- Sample Data
Enter one set of numbers in column A and the matching set of numbers in column B. So, in this instance,
Time is in column A and Ozone is in Column B, etc. (Note: you would get the actual numbers
by completing the lesson.)
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Graph Examples
Once the data is entered, highlight the data and allow the spreadsheet program
create a graph. The graphing command will vary from program to program so make sure to review the
program instructions. Select the type of graph you want the spreadsheet program
to create. Select one of the following examples:
Helpful Graphing Tips
- Graphing Ozone
- Bar Graphs: When graphing ozone data (colors and AQI averages) use bar graphs. Plot
the AQI average value versus Time.
| Ozone Condition |
Color |
AQI Average Value |
| Good |
Green |
25 |
| Moderate |
Yellow |
75 |
| Unhealthy
for Sensitive |
Orange |
125 |
| Unhealthy |
Red |
175 |
|
Very
Unhealthy |
Purple |
250 |
| Hazardous |
Maroon |
300 + |
- Graphing
Temperature
When graphing temperature, graph the hourly Fahrenheit reading versus
Time. Make sure to use the same format used to graph the Ozone
data. This will make the final analysis of the data easier
for the students.
- Wind Speed
When graphing the hourly wind speed, graph the mph reading versus Time.
Once again, use the same graphing format for data analysis purposes.
- Graphing
Cloud Cover/Conditions (Sunlight) - optional
This graph can be optional. If the skies were reported as
"clear" for every hour, it is really not necessary to create a graph
representing a straight line.
If it is
necessary to graph the observed sky conditions versus Time, make sure to use
the following chart. The chart lists the various sky conditions
(terminology may be subjective) with a
numerical value associated with each condition to ease the students' ability
to graph the data.
The data will come from the Weather Underground site,
specifically, the "Conditions" column. The
"Conditions" refer to the Cloud Cover visible in the sky. The
amount of Cloud Cover is often judged by the scale below and expressed in one
of four terms, Clear, Scattered, Broken, and Overcast. For graphing
purposes, the terms need to be expressed with a numerical value. The
chart below should assist with the conversion task. In addition to
explaining the conversion to your students, it may also be necessary to point
out that the amount of cloud cover has a direct relationship with the amount
of sunlight, and the amount of sunlight has a direct relationship with the
amount of ground level ozone generated during the day.
| Cloud
Cover/Conditions |
% Cloud Cover |
| Clear |
0% > 10% |
| Scattered (includes
Partly Cloudy) |
10% - 50% |
| Broken (includes Mostly
Cloudy) |
50% - 90% |
| Overcast |
90% + |
EPA | NESCAUM |
CIESE | Stevens Institute of Technology
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