After students have collected their data the next step is to analyze it. The goal of data analysis is to determine if there is a relationship between the independent and dependent variables. In student terms, this is called “looking for patterns in the data.” Did the change I made have an effect that can be measured?
Recording data on a table or chart makes it much easier to observe relationships and trends. For example, look at the following data table.
|Time||A Plants (12 hours light)||B Plants (8 hours light)||C Plants: (4 hours light)|
|Day||Height (cm)||Leaves||Height (cm)||Leaves||Height (cm)||Leaves|
Students may notice how in all of the plant samples, as the plant height increases, more leaves are produced. Students may also observe how the plants receiving only four hours of light (C Plants) produced less than half the amount of leaves at the end of 40 days than the plants receiving 12 hours of light (A Plants). There are so many observations that students might make when looking at their data tables! Comparing mean average or median numbers of objects, observing trends of increasing or decreasing numbers, comparing modes or numbers of items that occur most frequently are just a few examples of quantitative analysis.
Besides analyzing data on tables or charts, graphs can be used to make a picture of the data. Graphing the data can often help make those relationships and trends easier to see. Graphs are called “pictures of data.” The important thing is that appropriate graphs are selected for the type of data. For example, bar graphs, pictographs, or circle graphs should be used to represent categorical data (sometimes called “side by side” data). Line plots are used to show numerical data. Line graphs should be used to show how data changes over time. Graphs can be drawn by hand using graph paper or generated on the computer from spreadsheets for students who are technically able.
Here is what a graph of some of the data from the tomato table looks like. Notice how much easier it is to see the trends in the data here than in the data table.
You can use these questions to help guide students in analyzing their data:
After analyzing the data, students will be able to answer these questions as they draw some conclusions. Encourage students not to change their hypothesis if it does not match their findings. The accuracy of a hypothesis is NOT what constitutes a successful science fair investigation. Rather, Science Fair judges will want to see that the conclusions stated match the data that was collected.
Application of the Results: Students may want to include an application as part of their conclusion. For example, after investigating the effectiveness of different stain removers, a student might conclude that vinegar is just as effective at removing stains as are some commercial stain removers. As a result, the student might recommend that people use vinegar as a stain remover since it may be the more eco-friendly product.
In short, conclusions are written to answer the original testable question proposed at the beginning of the investigation. They also explain how the student used science process to develop an accurate answer.