**Graphing Tips and Examples:**

- 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.)

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:

**Bar Graph Examples**

**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% + |