Positive and Negative Controls
This is part of the NSW HSC science curriculum part of the Working Scientifically skills.
Introduction to Controls in Scientific Experiments
In the world of scientific experimentation, especially for high school students beginning to explore complex scientific concepts, understanding controls is essential. Controls are standard benchmarks used in experiments to ensure that the results are due to the factor being tested and not some external influence. There are two main types of controls: positive and negative.
Note that controls and controlled variables are different aspects of experiments.
Positive controls are used in experiments to show what a positive result looks like. They ensure that the testing procedure is capable of producing results when the expected outcome is present. They involve using a material or condition known to produce a positive result.
Positive controls confirm that the experimental setup can detect positive results and that all reagents and instruments are functioning correctly and as intended.
Negative controls, on the other hand, are used to ensure that no change is observed when a change is not expected. They help confirm that any positive result in the experiment is truly due to the test condition and not due to external factors.
Why Do We Use Positive and Negative Controls?
Rule Out False Positives: Negative controls help in ruling out the possibility that external factors are causing the observed effect.
No Expected Outcome: These controls involve using a material or condition known not to produce the effect being tested.
Validity and Reliability: Positive and negative controls are crucial for establishing the validity and reliability of an experiment. They provide a way of checking whether the experimental method actually tests the what it's supposed to test, and a basis for comparison to the experimental group.
Error Identification: Controls can help identify errors in the experimental setup or procedure, ensuring that the results of an experiment are due to the variable being tested.
Interpretation of Results: Understanding what constitutes normal variation in an experiment is essential for accurately interpreting results.
Example of Controls in Chemistry
Experiment: Testing the Presence of Vitamin C in Fruit Juice
Aim: To determine whether a particular fruit juice contains Vitamin C.
Positive Control: For this experiment, a known Vitamin C solution can be used. This solution should react positively with the testing reagent (like DCPIP, which changes colour in the presence of Vitamin C) to show that the test can indeed identify Vitamin C when it is present.
Negative Control: Distilled water serves as an effective negative control. It does not contain Vitamin C and should not react with the testing reagent. Any change in the negative control indicates contamination or an error in the experimental procedure.
Example of Controls in Physics
Experiment: Investigating Newton's Second Law of Motion
Aim: To verify Newton's Second Law of Motion, which states that the acceleration of an object is directly proportional to the net force acting on it and inversely proportional to its mass (`F = ma`).
Students use a dynamic cart on a track, a set of known masses, a pulley system, and a force sensor or photogate timer to measure acceleration.
- Positive Control: To ensure that the experimental setup can correctly measure force and acceleration, use a known mass and a predetermined force where `F = ma` can be accurately calculated. This setup should produce a predictable acceleration. When the experiment is conducted with these known values, the measured acceleration should closely match the theoretical acceleration calculated. This confirms that the equipment (force sensor, photogate timer, etc.) is functioning correctly and the experimental procedure is valid.
- Negative Control: To ensure that the measured acceleration is solely due to the applied force and not any other factors like friction or air resistance, conduct an experiment with no external force applied (other than the minimal force to overcome static friction). This can be done by using a dynamic cart on a level track without adding any additional weights or forces. The cart should exhibit minimal to no acceleration, indicating that any acceleration measured in the main experiment is due to the applied force and not inherent biases or errors in the setup.