Grand-slam data display: follow our game plan for making data tables, graphs, and charts.
Say your experiment is going to compare your favorite after-school activities: practicing moves on your Rollerblades, lifting weights to ge "buff," and rooting for your favorite baseball team during the World Series You want to know which of these activities gets your heart racing fastest.
The first step is to make a data table. A data table gives you a place to record your findings while you do your experiment. That's better than scribbling numbers on your hot dog napkin and trying to set the score straight later. So pull out some paper and pencils and let's get started.
On your data table you'll want to include all the variables in your experiment - your independent variable (type of activity); all the levels, or variations, of your independent variable (resting, Rollerblading, weight lifting, an watching the World Series); and your dependent variable (heart rate).
Once your table is lined your experiment and fill in the blanks with data. Gather your equipment and follow the rules for the "Roll, Lift, Relax Test" (right).
Just Graph IT!
When you're finished with the experiment, you'll have a table full of heart-pounding data. But all those numbers may seem out of your league unless you shape them up into something you can easily understand. How about a picture - a graph? Graphs can help you see trends in your data that might otherwise be hard to spot. The kind of graph you make depends on your data. For the heart-rate experiment above, a bar graph would be best. That's because the indepedent variable (type of activity) is a discrete variable, a variable that has levels which are distinct and unconnected. Resting, Rollerblading, weight lifting,and watching TV are all different kinds of activities. On a bar graph, the result for each value of the independent variable is represented by a separate, or discrete, bar.
But what if you decide to find out how your heart rate changes as you increase the time you spend doing each activity? Your independ variable has now changed from "type of activity" to "time."
Time is a continuous variable. In the other words, if you measured your heart rate after Rollerblading for 2 minutes, 4 minutes, and 6 minutes, . there are other times in between these (e.g., 3 minutes and 5 minutes). A line graph, which is made of a continuous line, can help you estimate what your heart rate would be for those in-between values.
As your heart slows down to its resting rate and you finish up your graphs, you start to wonder: Which of these three activities do kids like best? To find out, you conduct a survey in your school. our results show that 40 percent of those watching the World Series; 50 percent prefer Rollerblading; and 10 percent like lifting weights best. To show the crowd exactly what these data mean, make a pie chart. That's the best way to present data that are percentages of a whole. A pie chart is basically a circle divided into wedge-shaped sections. The trick is that the size of each wedge represents a piece of data. So the wedge for watching the World Series should take up 40 percent of the circle, and so on.
If all this info makes you want to head for the showers, relax: Even Ken Griffey Jr. didn't get to the major leagues overnight. You can review our lineup of data-display choices after you finish our project (see "How to Make Charts and Graphs," right). You an probably think of other creative ways to display your data, through pictures, maps, or charts. Just remember the ultimate goal: to help your understand the research you did - and to show off your home-run results.
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|Title Annotation:||Special Issue: Science Project Success Guide; organize your data; includes related articles on charts and graphs|
|Date:||Sep 20, 1996|
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