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April 28, 2024, 09:22:18 pm

Author Topic: Valid and Fair?  (Read 638 times)  Share 

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psyxwar

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Valid and Fair?
« on: March 24, 2013, 10:27:42 am »
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I'm a little confused as to what these term mean. Does valid mean that your experimental design actually tests your hypothesis (ie. that you're testing the right variables) and fair mean that all extraneous variables are kept constant throughout the experiment?
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Yacoubb

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Re: Valid and Fair?
« Reply #1 on: March 24, 2013, 10:37:44 am »
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Yeah that's correct. Fair means every participant has an equal chance in the experiment, and the reliability of your findings is increased by controlling all these extraneous variables. You also should repeat the experiment as this increases reliability   decreases chance of systematic-random error

psyxwar

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Re: Valid and Fair?
« Reply #2 on: March 24, 2013, 10:52:17 am »
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Yeah that's correct. Fair means every participant has an equal chance in the experiment, and the reliability of your findings is increased by controlling all these extraneous variables. You also should repeat the experiment as this increases reliability   decreases chance of systematic-random error
Thanks. Does repetition decrease the chance of a systematic error though? Because if say, a scale isn't zeroed properly, that would affect all your results, regardless of how many times you repeat it.
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Yacoubb

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Re: Valid and Fair?
« Reply #3 on: March 24, 2013, 02:11:35 pm »
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Thanks. Does repetition decrease the chance of a systematic error though? Because if say, a scale isn't zeroed properly, that would affect all your results, regardless of how many times you repeat it.

Sorry for the misleading statement. I meant that you should repeat the experiment to increase the reliability of your findings because you decrease the chances of random errors. You should also control your systematic errors because they can actually decrease the reliability. If you were observing the net movement of water into a dialysis tube, and your #1 measurement reading was 1 or 2g higher than its actual mass, you're bound to come to wrong conclusions.