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Drawing Conclusions and Identifying Bias and Errors…. A good experiment is designed so the experimenter can reach a valid conclusion. A valid conclusion is one the experimenter and other people can trust.
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A good experiment is designed so the experimenter can reach a valid conclusion. A valid conclusion is one the experimenter and other people can trust.
Conclusions can be trusted if no error occurred during the experiment. Errors may include misinterpreting the cause of an effect, or carrying out a faulty procedure. • Bias can also lead to error. • Bias is a wish, conscious or unconscious, to have an experiment lead to a certain conclusion.
Drawing Conclusions • An experiment is conducted to test a hypothesis. • A conclusion states whether the results of an experiment support the hypothesis. The conclusion should take the independent and dependent variables into account. In other words, the conclusion should state whether and how the dependent variable changed as the independent variable was manipulated.
Example: You test a hypothesis that increasing the temperature of a gas changes the volume of the gas. In your experiment, you measure and record the volume of a certain amount of gas at different temperatures.
By studying the data presented in the graph, you can conclude that the data support your hyypothesis. As temperature increases, the volume of the gas also increases. This conclusion relates how the dependent variable (volume changed asa result of the changes in the independent variable and the dependent variable is a cause and effect relationship. Increasing temperature causes the volume of a gas to increase.
From this information, you can also make predictions. If you look at the graph, you can predict the volume of the gas at temperatures in between the points you have measured. You simply draw a new point on the line. Then you read directly down to find the new temperature. Although you have not measured volume t that temperature, you can be fairly confident of what the volume should be.
When scientist publish the results of their research, they do more than present their data. It is important to describe procedures accurately. This allows other scientists to repeat the experiment that were conducted by someone else, they are checking the first set of results, all the results support the same conclusion.
Experimental Error • In another scientist repeats the experiment and gets different results, the scientists have to figure out why. • They will examine the methods they used in order to see whether differences in results. One o the scientists may have made mistakes. It is important to assess experiment critically and to be as free of bias as possible. Carefully considering the ideas presented by other scientists will allow for a greater understanding of the processes that were followed and the data that resulted.
An experiment can also produce false results. • These results are often cause by the experimental error. • Experimental error is a mistake in an experiment that can lead to false results.
Experimental error can be a mistake made by the experimenter. • These errors include measuring incorrectly or following the procedure incorrectly. • Experimental error can also be caused by an independent variable that was not controlled during the experiment.
The design of the experiment might have introduced two independent variables. • In the experiment described before, let’s say both temperature and pressure changed during the experiment. Theexperimenter could not tell which of the independent variable caused the change in volume. It could have been either variable, or both of them.
Guarding against bias Bias is not always conscious. People may expect or want their ideas to be valid, because they do not like being wrong. In some cases there are other reason
For example: • A team that invents and tests a new drug wants it to work. A cure for a disease can help many people. It may also make its inventors rich or famous.
Scientists who are aware of their biases can be particularly careful to check their results. • Hypotheses testing and using a control group help fight bias. • Careful observation is also important.
When testing a drug, the researchers will not just note that a patient said he felt better. They will also measure and record the patient’s symptoms and lab results. • Another way to fight bias is double-blind testing. In those experiments, neither the patients nor the researchers know who is in the experimental group.
The control group gets pills or injections that do nothing and look like the real drug. This avoids some experimental errors. • People who know they are getting a drug are likely to feel better. Also, researchers may think a patient who they know got the drug is healthier than one who did not. • After conducting the experiment and recording the results, the scientists look up which patients got the drug. This helps them reach a valid conclusion.
Suppose you have a cold and someone tells you to drink this tea. If you wake up in the morning and feel better, you might tell everyone it was because of the tea, however, this is not a valid conclusion.
What should you do if your conclusion does not support your hypothesis?
