A data table is a group of related facts arranged in labeled rows and columns and is used to record information. Its purpose is to help sort, analyze and compare data gathered from a science experiment or research project. Knowing how to create a data table demonstrates skills in organizing information in a meaningful way and provides a learning base to progress to more sophisticated ways to track data.
Components of a Data Table
All data tables should have the following components:
The title describes the variables and what is being measured. If you are constructing a data table comparing different types of activities on heart rate, your title would read “The Effect of Different Physical Activities on Heart rate”
All data tables have at least one independent variable and at least one dependent variable. If you are doing a science experiment, your data table should also have a control, something that will not change or be manipulated. The “control” in our heart rate example would be a resting heart rate.
A variable is something that is capable of being changed and this is what you measure. There are two types of variables: The independent variable is the variable that you can control or manipulate. The dependent variable is the variable that changes as a result of you manipulating or changing the independent variable.
For example, in the exercise/heart rate table, your independent variable would be the type of exercise (yoga, weightlifting, running or walking) and your dependent variable would be the heart rate. Label your dependent and independent variables on the appropriate axis of the data table. “Type of Activity” would be the header for the vertical axis and “Heart rate (beats per minute) would be the header for the horizontal axis.
For the data table to have meaning, use a measurable unit to compare the two variables. Examples of measurable units would be time (hours, minutes, seconds), length (centimeters, inches, miles) or degrees (Fahrenheit, Celsius). In our example, we are comparing the effect of four different types of activities on heart rate, so we would use beats per minute as our unit of measure.
When comparing the variables, include at least three trial runs for each activity. Conducting more than one trial helps you to find an average and reduces the possibility of experimental error. For example, measure the heart rate for “walking” at least three different times. After completing three “walking” trials, total the heart rates, then divide it by three (or number of times you did the trials) to get an average heart rate for the walking activity. Repeat this step for each activity.
Setting up the Table
- Using a ruler for a straight edge, draw a grid leaving enough spaces for the data.
- At the top of the data table, write your title identifying the variables and what you are measuring (effect of activity on heart rate)
- Label column on the left with the independent variable or what will change (different activities: running, yoga, walking….)
- Label the columns to the right the dependent variables (the measurable effect resulting from changing the independent variable). The dependent variable would be the number of beats per minute for each activity. Remember to include enough space to record a minimum of three trial measurements (beats per minute) for each activity as well as a space to record the average beats per minute for that activity.
- Collect data and record in the appropriate box.
- Check data table for completeness or errors.
Practice Creating Your Own Table Using the Following Data:
Title: Effect of Different Physical Activities on Heart Rate
Dependent variable: Heart Rate (measured in beats per minute)
Independent Variable: Type of Activity (running, weightlifting, walking, yoga)
Three trials and average for each activity measured in beats per minute:
Running: 162, 168, 174, avg: 168
Weight Lifting: 140, 158, 151, avg: 149
Walking: 110, 115, 108, avg: 111
Yoga: 102, 94, 98, avg: 98
Note: control for heart rate is measured at 68, 72, 70, with average of 70 bpm.
To see how you did, click here to view and download this data table, and then compare your results