Lab Report Data does not fit hypothesis

[Guest]

I'm doing a practice IA and my data does not fit the hypothesis. In the mark scheme, it says that we need justification for our conclusion - does this mean that I need to find a resource that shares the same trend? Or can I just state that our data did not fit the trends of x sources and state it would be due to the problems mentioned in the evaluation?

Any help would be greatly appreciated!

Edited April 1, 2016 by Guest

[Vioh]

9 hours ago, apoello said:

I'm doing a practice IA and my data does not fit the hypothesis. In the mark scheme, it says that we need justification for our conclusion - does this mean that I need to find a resource that shares the same trend? Or can I just state that our data did not fit the trends of x sources and state it would be due to the problems mentioned in the evaluation?

If your data doesn't support your hypothesis, then there can only be three reasons: (1) your method is wrong, (2) you have systematic errors in your experiment which led to the wrong results, and (3) your hypothesis is wrong.
Go through the steps of your experiment again, and try to find any systematic errors that could possibly occur. If there are indeed systematic errors in your experiment and you know that these systematic errors are why you got the wrong results, then you can write exactly that in the "conclusion and evaluation" part.
However, if you couldn't find any systematic errors, or if you found some, but none of them could possibly lead to the wrong results, then you'd better check your hypothesis again. Does your hypothesis really follow the theories that you have learned in class? If no, fix your hypothesis. But if the answer is yes, then maybe you've just made a new discovery (). In that case, try to find a published scientific paper that got the same trend. If there isn't, then you should mention that "more future experiments need to be done in order to confirm the results".

[Guest]

1 hour ago, Vioh said:

If your data doesn't support your hypothesis, then there can only be three reasons: (1) your method is wrong, (2) you have systematic errors in your experiment which led to the wrong results, and (3) your hypothesis is wrong.
Go through the steps of your experiment again, and try to find any systematic errors that could possibly occur. If there are indeed systematic errors in your experiment and you know that these systematic errors are why you got the wrong results, then you can write exactly that in the "conclusion and evaluation" part.
However, if you couldn't find any systematic errors, or if you found some, but none of them could possibly lead to the wrong results, then you'd better check your hypothesis again. Does your hypothesis really follow the theories that you have learned in class? If no, fix your hypothesis. But if the answer is yes, then maybe you've just made a new discovery (). In that case, try to find a published scientific paper that got the same trend. If there isn't, then you should mention that "more future experiments need to be done in order to confirm the results".

It's definitely the systematic errors - thank you!  Just wondering though, you wouldn't mention the specifics of the errors in the conclusion though, right? Would you put in a note to refer to the evaluation?

[Vioh]

54 minutes ago, apoello said:

It's definitely the systematic errors - thank you!  Just wondering though, you wouldn't mention the specifics of the errors in the conclusion though, right? Would you put in a note to refer to the evaluation?

I would recommend you to put everything under the section "Conclusion and Evaluation". This is because both are definitely related in your case.

[kw0573]

IB expects that if the error is from not following procedures carefully (eg didn't calibrate a device), then you should repeat the experiment. If it's an error you have only found out after doing the analyses or after the experiment then it's sufficient to outline potential errors and improvement methods in Conclusion and Evaluations. A quite successful evaluation will outline very plausible improvements in methodology, rather than not mentioning any improvements at all.

Quote

Strengths and weaknesses of the investigation, such as limitations of the data and sources of error, are discussed and provide evidence of a clear understanding of the methodological issues* involved in establishing the conclusion. The student has discussed realistic and relevant suggestions for the improvement and extension of the investigation.

The above is a selected description for highest level in Evaluation (5-6 / 6) in the newest physics guide (2016).

[Guest]

5 hours ago, kw0573 said:

IB expects that if the error is from not following procedures carefully (eg didn't calibrate a device), then you should repeat the experiment. If it's an error you have only found out after doing the analyses or after the experiment then it's sufficient to outline potential errors and improvement methods in Conclusion and Evaluations. A quite successful evaluation will outline very plausible improvements in methodology, rather than not mentioning any improvements at all.

The above is a selected description for highest level in Evaluation (5-6 / 6) in the newest physics guide (2016).

As it's just a practice IA I'm hoping our teacher won't mind if we don't repeat the experiment, but other than that, got those down.

12 hours ago, Vioh said:

I would recommend you to put everything under the section "Conclusion and Evaluation". This is because both are definitely related in your case.

Thank you both for your help!