You may find the answer to your question in this website:
http://answers.yahoo.com/question/index?qid=20080615165001AABZ33w
Copy paste it:-)
experimental control
The experimental control is what you compare your experimental data with. Without the control, you can't tell if the variable you are testing is what is causing your results.
experimental control
Positive control in experimental control refers to a group or condition that is expected to produce a known response or effect, thereby validating the experimental setup and ensuring that the methodology is working as intended. It serves as a benchmark to confirm that the experimental conditions can detect what they are supposed to measure. By comparing experimental results to the positive control, researchers can ascertain the reliability and accuracy of their findings.
EXPERIMENTAL SET UP * involves the set up that will allow you to investigate what you are interested to know. CONTROL SET UP * involves a set up that is exactly the same as the experimental, except the factor that you hypothesis to influence the results.
control setup
pure -absolute control Quasi -have some control
In a Redis experiment, the control setup typically involves a baseline configuration where Redis is run without any experimental modifications or enhancements. This includes using default settings for parameters like memory management, persistence, and replication. The control setup allows for comparison against experimental setups that might involve changes such as different data structures, configurations, or performance optimizations to assess their impact on Redis's performance and behavior. By establishing a control, researchers can better isolate the effects of the variables being tested.
the control group does not receive receive an experimental treatment but stay in the same environment.
A control sample or control group is used to compare with the experimental group or sample. The control sample ideally, should be exactly the same as the experimental sample except that you don't give your experimental treatment to the control sample. Afterwards you compare the 2 samples to see if your experimental treatment had any kind of effect. The control is like a reference point.
Maintaining the same temperature for both the control and experimental setups is crucial to ensure that temperature-related variables do not influence the results. Temperature can affect the rate of chemical reactions, biological processes, and physical properties of materials, potentially skewing the data. By controlling this variable, researchers can isolate the effects of the experimental treatment and draw more accurate conclusions about its impact. Consistency in temperature helps enhance the reliability and validity of the experiment.
control groups are those which you keep constant you don't do anything to them and experimental groups are the ones which you are adding something to it to see what happens