BIOL 1406
PreLab 2.7
How can I use tables or spreadsheets to analyze the relationship between 2 experimental variables?
Scientists are often interested in studying the relationship between 2 experimental variables. For example:
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To examine some methods scientists use to analyze the relationship between experimental variables, let’s look at an example where a scientist is studying the relationship between the protein concentration of a solution and the amount of UV light at 280 nm that the solution will absorb. To study this relationship, the scientist prepares 9 solutions with the following protein concentrations in μg/mL: 0, 10, 20, 40, 80, 160, 320, 640, and 1280. He then places each solution in a spectrophotometer and measures the absorbance of UV light at 280 nm. He records the following A280 values: 0.000, 0.045, 0.098, 0.195, 0.373, 0.711, 1.398, 1.833, and 1.999. Notice that the data this scientist collects will consist of pairs of values. For each observation, he records both the concentration of the solution, and the A280 value of the solution. Since both concentration and the A280 values can change as he makes his observations, they are both variables. However, note that before the experiment even starts, the scientist must decide which protein concentrations he wishes to test. Because the concentration of each solution was determined beforehand by the experimenter and did not depend, in any way, on the A280 values of the solutions or on any other variables in the experiment, it is called an independent variable. On the other hand, the A280 values are not determined by the experimenter. These values depend on the experimental conditions that have been set up. Therefore, the A280 variable is called a dependent variable. In general, the results you record at the end of the experiment are the values of your dependent variable.
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YOUR TURN | ||
For each example below, identify the independent and dependent variables: | ||
Example #1 - A botanist measures the height of four groups of pea plants that are grown using different concentrations of a nutrient solution. She takes her measurements once per week over the course of 3 months. | ||
Which is/are independent variable(s)? | Hint | Check your answer. |
Which is/are dependent variable(s)? | Hint | Check your answer. |
Example #2 - A scientist studies the survival rate of 4 groups of AIDS patients. One group receives no drug treatment, the second group receives the drug AZT only, the third group receives the drug saquinavir (a protease inhibitor) only, and the fourth group receives both AZT and saquinavir. The survival rate is recorded once per month over the course of 2 years. |
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Which is/are independent variable(s)? | Hint | Check your answer. |
Which is/are dependent variable(s)? | Hint | Check your answer. |
Often, the first step in analyzing the relationship between two experimental variables is to organize your data in a table or spreadsheet. A table or spreadsheet is an orderly presentation of data aligned in rows and columns. Data for paired variables are conveniently shown in a table with 2 columns. Values for the independent variable are usually shown in the left column while the corresponding values for the dependent variable are shown in the right column. The following table presents hypothetical results for the scientist who is studying the possible relationship between protein concentration and A280 values:
Table 2.1 Absorbance of UV light by protein solutions |
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Protein Concentration (μg/mL) |
A280 |
1. The table
should be self explanatory. In other words, the table should have a
descriptive title and all parts of the table should be clearly labeled so
that the reader knows exactly what every number or entry in the table
represents. 2. All measurements listed in the table should include appropriate units. (Note, however, that absorbance values are unusual in that they are one of the few measurements that lack units.) |
0 | 0.000 | |
10 | 0.045 | |
20 | 0.098 | |
40 | 0.195 | |
80 | 0.373 | |
160 | 0.711 | |
320 | 1.398 | |
640 | 1.833 | |
1280 | 1.999 |
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