I always lose marks in homeworks for the reasoning the anomalous results. It's normally the only section I lose marks in, evaluation, and it's getting a bit annoying.
Let's this we're measuring temperature changing after a reaction is underway. Why might one get an anomalous result? Perhaps misreading the thermometer, or the stopwatch?
It seems to me if it was adding too much/little of a reactant would cause all results to be wrong..?
Yeah work on things like the human error you've mentioned
also if your measuring temperature changes think about stuff like if you're losing heat to the environment or whether your starting point was ACTUALLY the starting temperature
hope that helps....
- Stopwatch: Human error will be the most significant; your reaction time from when you first see whatever you're looking for to when you hit that button. That will also vary every time you do it. Minor to that is the instrumental error.
- Thermometer: ±0.5 if you're measuring in 1ºC intervals
- Mixing: Sometimes you have to mix the reactants...
Then you need to say how you can reduce your errors. Well instrumental aren't really that significant, you could measure to a higher degree of accuracy but that will only make a difference if your measurements are quite small, e.g. if you’re measuring temperature at 1 ºC intervals from 0-5 ºC, the error will be much more significant than the temperature from 400-405 ºC.
Human is difficult to overcome as well – if you’re working as a pair just make sure the same person is using the stopwatch every time. And for the end point – well if you’re looking for a colour change you could use a colorimeter or something, which would be more accurate in judging your end point. Or you could quench the reaction at different points and carry out a titration.
Method error – depends on your experiment really. Make sure that if you stir solution A 5 times, you stir solution B 5 times too . You might be able to think up a better way of conducting the experiment.
General - comment on number of repeats, exclude anomalous data if you have other sets of data that are better, take averages, compare to literature values, etc.
if its human error do it again or ignore it if its natural variation then its naturally like that so leave it alone and if its an unfair test then you start it again.
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