Collect Raw Data
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.)
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.
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