This step describes types of and ways to collect raw data (experimental results). Raw data includes observations (information collected about something by using your senses) made during testing. The two types of observations are qualitative and quantitative. A quantitative observation is a description of the amount of something. Numbers are used in quantitative descriptions. Instruments, such as a balance, a ruler, and a timer, are used to measure quantities or to describe the amount of the property being observed, such as mass, height, or time.
Metric measurements are generally the preferred units of measurement for science fair projects; for example, length in meters, mass in grams, volume in milliliters, and temperature in degrees Celsius. Another type of quantitative observation can be a scale that you design. For example, if your experiment involves measuring the change in the freshness of flowers, you might have a scale of freshness from 1 to 5, with 5 being the most fresh and having no dry parts on the petals and 1 being the least fresh with each petal being totally dry.
A qualitative observation is a description of the physical properties of something, including how it looks, sounds, feels, smells, and/or tastes. Words are used in a qualitative description. The qualitative description of a light could be about its color and would include words such as white, yellow, blue, and red.
As you collect raw data, record it in your log book. You want your log to be organized and neat, but you should not recopy the raw data for your journal. You should recopy the data that you will want to represent the information on your display in tables and/or graphs so that it is more easily understandable and meaningful to observers. (See chapter 10 for information about the project display.)
Tables
Data is generally recorded in a table, which is a chart in which information is arranged in rows and columns. A column is a vertical listing of data values and a row is a horizontal listing of data values. There are different ways of designing a table, but all tables should have a title (a descriptive heading) and rows and columns that are labeled. If your table shows measurements, the units of measurement, such as minutes or centimeters, should be part of the column's or row's label.
For an experimental data table, such as Table 8.1, the title generally describes the dependent variable of the experiment, such as "Moths' Attraction to Light," which in this case is for the data from an experiment where yellow and white lightbulbs (independent variable) are used and the number of moths attracted to each light is counted (dependent variable). In contrast, the title "White Light versus Yellow Light in the Attraction of Moths" expresses what is being compared. As a key part of the data organization, an average of each of the testings is calculated.
Analyzing and Interpreting Data
When you have finished collecting the data from your project, the next step is to interpret and analyze it. To analyze means to examine, compare, and relate all the data. To interpret the data means to restate it, which involves reorganizing it into a more easily understood form, such as by graphing it. A graph is a visual representation of data that shows a relationship between two variables. All graphs should have:
- A title.
- Titles for the x-axis (horizontal) and y-axis (vertical).
- Scales with numbers that have the same interval between each division.
- Labels for the categories being counted. Scales often start at zero, but they don't have to.
The three most common graphs used in science fair projects are the bar graph, the circle graph, and the line graph. Graphs are easily prepared using graphing software on a computer. But if these tools are not available to you, here are hints for drawing each type of graph.
In a bar graph, you use solid bar-like shapes to show the relationship between the two variables. Bar graphs can have vertical or horizontal bars. The width and separation of each bar should be the same. The length of a bar represents a specific number on a scale, such as 10 moths. The width of a bar is not significant and can depend on available space due to the number of bars needed. A bar graph has one scale, which can be on the horizontal or vertical axis. This type of graph is most often used when the independent variable is qualitative, such as the number of moths in Table 8.1. The independent variable for the Moths' Attraction to Light table is the color of light—white, yellow, or no light (control)—and the dependent variable for this data is the number of moths near each light. A bar graph using the data from Table 8.1 is shown in Figure 8.1. Since the average number of moths from the data varies from 1 to 12, a scale of 0 to 15 was used, with each unit of the scale representing 1 moth. The heights of the bars in the bar graph show clearly that some moths were found in the area without light and some near the yellow light, but the greatest number were present in the area with white light.
A circle graph (also called a pie chart) is a graph in which the area of a circle represents a sum of data, and the sizes of the pie-shaped pieces into which the circle is divided represent the amount of data. To plot your data on a circle graph, you need to calculate the size of each section. An entire circle represents 360°, so each section of a circle graph is a fraction of 360°. For example, data from Table 8.1 was used to prepare the circle graph in Figure 8.2. The size of each section in degrees was determined using the following steps:
- Express the ratio of each section as a fraction, with the numerator equal to the average number of moths counted on each type of light and the denominator equal to the average total number of moths counted on all the lights:
- Multiply the fraction by 360°:
White 12/17 × 360° = 254.1°
Yellow 4/17 × 360° = 84.7°
Control 1/17 × 360° = 21.2°
To prepare the circle graph, first decide on the diameter needed, then use a compass to draw a circle. Next draw a straight line from the center of the circle to any point on the edge of the circle. Using a protractor, start at this line and mark a dot on the edge of the circle 254.1° from the line. Draw a line to connect this dot to the center of the circle. The pie-shaped section you made represents the number of moths found near the white light. Start the next section on the outside line for the yellow light section. The remaining section will be the no-light section, or control section. Each section should be labeled as shown in Figure 8.2.
Each section of a circle graph represents part of the whole, which always equals 100%. The larger the section, the greater the percentage of the whole. So all of the sections added together must equal 100%.
To determine the percentage of each section, follow these steps:
- Change the fractional ratio for each section to a decimal by dividing the numerator by the denominator:
- Change the decimal answers to percent. Percent means "per hundred." For example, for white light, .70 is read 70⁄100 or 70 per 100, which can be written as 70%.
White light: .70 = 70/100 = 70%
Yellow light: .24 = 24/100 = 24%
Control: .06 = 6/100 = 6%
To represent the percentage of moths attracted to each light color, you could color each section of the circle graph with a different color. You could label the percentages on the graph and make a legend explaining the colors of each section as in Figure 8.3.
A line graph is a graph in which one or more lines are used to show the relationship between the two quantitative variables. The line shows a pattern of change. While a bar graph has one scale, a line graph has two scales. Figure 8.4 shows a line graph of data from a different study in which the problem was to determine if ants communicate by laying a scent trail for other ants to follow to a food source. The line graph shows data for the number of ants observed on one of the paths every 15 minutes for 1 hour. Generally, the independent variable is on the x-axis (the vertical axis) and the dependent variable is on the x-axis (the horizontal axis). For this example, the independent variable of time is on the x-axis and the dependent variable of number of ants is on the x-axis. One unit on the time scale represents 1 minute, and units are marked off in groups of 15 up to a total of 60 units. One unit on the number of ants scale represents 1 ant. Since the largest average counted was 32.2 ants, the scale for ants is numbered by fives from 0 to 35. On the graph, the increase in the angle of the line over time shows that more ants were found on the food as time increased.
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