Collecting data in any experiment involves making observations. You first must decide what type of data you must collect. Data (information) can be either quantitative or qualitative. All data is entered in ink into the Project Log Book.
Collecting quantitative data involves using scientific instruments to make measurements. Any measurement calculated in any scientific experiment always involves the metric system!! Never use yards, ounces, feet, inches, gallons, mph, or any other standard unit!! The data is usually collected and organized into a table so that it can be interpreted easily.
Some examples of quantitative data:
Collecting qualitative data involves involves making observations, but does not involve measurements. To collect and present data for a qualitative experiment, one must make a "rating scale" with specific definitions. For example, if an experiment was done on how different types of soft drinks effect the decay of teeth, there is not a "clear" way to "measure the decay of a tooth". One would have to take photographs of the teeth, and develop a specific rating scale defining the amount of decay. The rating scale would include numbers which could be graphed. See the example below.
- 0- no decay present (no color change and no change in texture and hardness of the tooth)
- 1-slightly decayed (slight color change or change in texture, tooth has become slightly softer)
- 2- moderate decay (definite color change or change in texture, tooth is moderately softer)
- 3-prominent decay (drastic color change and change in texture, tooth is very soft)
Observations: Collecting data in any experiment involves observations. Observations can be written descriptions of what you noticed during the experiment or it can be in the form of quantitative raw data. Every project should include both types of observations. Experiments are often done in series. A series of experiments can be done by changing the independent variable a different amount each time. A series of experiments is made up of separate experimental trials. During each trial, after you have changed the amount of the independent variable, you make a measurement of how much the independent variable affected the system under study. You record this measured response into an observation table. This is considered "raw data", since it has not been processed or analyzed. When "raw data" gets processed mathematically it becomes results and is entered into a data table.
Data Tables: Once your calculations are complete you enter your results into a data table. It is this information that is used to draw your conclusion. All tables must have a title. An accepted method is- The Effect of (the independent variable) on the (dependent variable). For instance; The Effect of Different Nitrogen Levels on the Amount of Fruit Produced in Tomato Plants. In the table itself, the independent variable is located on the far left column. The dependent variable is recorded on the right side of the table. All of the individual trial results including units are entered here. The last column is where the average for the trials is recorded. This mathematical average is what is shown in the graph, not the individual trial data. Please see the attached sample.
Graphs: Graphs are a visual display of your data, and are useful in illustrating what happened during your experiment. The graph shows the relationship between one variable to another. Three types of graphs can be used. Line graphs show trends or how the data changed over time. Bar graphs are useful for comparing information collected by counting. Pie graphs are used to show how some fixed quantity is broken down into parts (percentages). Please use the Skills Handbook located in the back of your textbook for further instructions. The same main title used for the data table is used for the graph, a subtitle may be added to further describe the graph. It is very important to correctly label the graph. The independent variable is always located on the horizontal or x axis. The dependent variable is located on the vertical or y axis. Be sure to include the correct metric units on your graphs. All data tables and graphs must be completed on the computer.