Practical terminology
Here is a list of some basic science terminology which is used in most practical experiments.
Please correct me if any of these are incorrect, or post any examples that you may find easier to understand. Thanks J
There are 3 types of variables- Independent, dependent and controlled.
Here I will use a example experiment that I did in Biology (The first prac dot-point) –‘testing different substrate concentrations and its effect on the activity of an enzyme’ (a.k.a Milk and Rennin test)
Independent variable- the variable that you change, which affects the dependent variable. There should only ever be ONE independent variable, all others must be controlled.
E.g. Other potential independent variables in this experiment may also include changing in pH or temperature.
Controlled variables- variables that must be constant and controlled to ensure that the experiment is only testing the change in ONE variable (the independent variable).
E.g. If I’m testing the substrate concentration’s effect on the catalyst, the pH and temperature must always start on the same value for each trial.
Dependent variable- Variable that is determined by the independent variable. It’s value depends on the change of the independent variable. It is usually what you try to find (the objective of the experiment).
E.g. We are trying to find the “substrates concentration’s effect on the activity of an enzyme”. So the activity of an enzyme depends on the substrates concentration. Our dependent variable here is the enzymes activity, or reaction rate to the substrate.
Control- An exact replica of the initial experiment, but with no independent variable. All variables are controlled. It is used as a comparison to the experiment that does use the independent variable. This is to determine that it is the independent variable that influences the reaction, not some other factor.
E.g. A control for this experiment would be a beaker with no substrate added to it. This takes away the independent variable and can be used to compare with the beaker that had the substrate added.
Some other important terms that you may come across are accuracy, reliability, and validity.
Accuracy- closeness to the true value
E.g. Measuring millimeters with a meter ruler reduces accuracy. With a ruler having a centimeter grade, there will be ± 10mm (1%) inaccuracy.
Reliability (reproducibility)- consistency or repeatability.
E.g. If 99% of my basketball free throws hit the rim every time, you can rely on my next shot to hit the rim also. You could say I’m consistently inaccurate. Therefore its possible to be inaccurate and reliable, but not the other way around.
Validity- fairness of experiment
E.g. If I was to determine that a Drug A gave a particular effect, I would have days I take Drug A, and days I do not (control). If I happen to have a headache, so I take another drug (Drug B), this would make the test invalid, as there is more than one independent variable.
Common errors
Systematic error- not taking a measurement from zero. E.g. not transferring all of a solution from one beaker to another can lead to incorrect measurements.
Random error- parallax error or using incorrect measuring equipment.
Improving reliability, validity and accuracy- for an experiment to be successful, all of these components must be met.
To improve accuracy, make sure that all measuring equipment can accurately measure the correct units needed (E.g. cm or mm.), and that all substances are properly transferred to reduce systematic errors.
To improve reliability, you have to reduce the spread of results. This includes taking large sample sizes, then taking the average of the results.
To improve validity, you have to make sure that there is a control, and that only one independent variable is tested at a time. The experiment also has to be appropriate to the aim, using appropriate subjects and conditions.
Hope this helps, any comments or suggestions will be much appreciated.
Here is a list of some basic science terminology which is used in most practical experiments.
Please correct me if any of these are incorrect, or post any examples that you may find easier to understand. Thanks J
There are 3 types of variables- Independent, dependent and controlled.
Here I will use a example experiment that I did in Biology (The first prac dot-point) –‘testing different substrate concentrations and its effect on the activity of an enzyme’ (a.k.a Milk and Rennin test)
Independent variable- the variable that you change, which affects the dependent variable. There should only ever be ONE independent variable, all others must be controlled.
E.g. Other potential independent variables in this experiment may also include changing in pH or temperature.
Controlled variables- variables that must be constant and controlled to ensure that the experiment is only testing the change in ONE variable (the independent variable).
E.g. If I’m testing the substrate concentration’s effect on the catalyst, the pH and temperature must always start on the same value for each trial.
Dependent variable- Variable that is determined by the independent variable. It’s value depends on the change of the independent variable. It is usually what you try to find (the objective of the experiment).
E.g. We are trying to find the “substrates concentration’s effect on the activity of an enzyme”. So the activity of an enzyme depends on the substrates concentration. Our dependent variable here is the enzymes activity, or reaction rate to the substrate.
Control- An exact replica of the initial experiment, but with no independent variable. All variables are controlled. It is used as a comparison to the experiment that does use the independent variable. This is to determine that it is the independent variable that influences the reaction, not some other factor.
E.g. A control for this experiment would be a beaker with no substrate added to it. This takes away the independent variable and can be used to compare with the beaker that had the substrate added.
Some other important terms that you may come across are accuracy, reliability, and validity.
Accuracy- closeness to the true value
E.g. Measuring millimeters with a meter ruler reduces accuracy. With a ruler having a centimeter grade, there will be ± 10mm (1%) inaccuracy.
Reliability (reproducibility)- consistency or repeatability.
E.g. If 99% of my basketball free throws hit the rim every time, you can rely on my next shot to hit the rim also. You could say I’m consistently inaccurate. Therefore its possible to be inaccurate and reliable, but not the other way around.
Validity- fairness of experiment
E.g. If I was to determine that a Drug A gave a particular effect, I would have days I take Drug A, and days I do not (control). If I happen to have a headache, so I take another drug (Drug B), this would make the test invalid, as there is more than one independent variable.
Common errors
Systematic error- not taking a measurement from zero. E.g. not transferring all of a solution from one beaker to another can lead to incorrect measurements.
Random error- parallax error or using incorrect measuring equipment.
Improving reliability, validity and accuracy- for an experiment to be successful, all of these components must be met.
To improve accuracy, make sure that all measuring equipment can accurately measure the correct units needed (E.g. cm or mm.), and that all substances are properly transferred to reduce systematic errors.
To improve reliability, you have to reduce the spread of results. This includes taking large sample sizes, then taking the average of the results.
To improve validity, you have to make sure that there is a control, and that only one independent variable is tested at a time. The experiment also has to be appropriate to the aim, using appropriate subjects and conditions.
Hope this helps, any comments or suggestions will be much appreciated.
Last edited:
