Lab Report Measuring Lab

[YeunJi Lee]

Hi, in my chemistry class, I'm doing a measuring lab, figuring out which equipment is the most accurate among graduated cyllinder, burette, graduated pipette and volumetric pipette. And I'm assessed on DCP and conclusion.

1) For presenting raw data, can I put 4 different tables like this (only one of them is presented below), not just one big table? Because if I put them all in one, I don't know how to handle the uncertainties... It just doesnt fit.

Table 4: Volumetric Pipette

Volume of water in conical flask (ml) Masses of the conical flask and of water (g)

0 175.433

25 200.753

50 225.719

75 250.829

100 275.655

125 300.537

2) For presenting raw data, I should include both qualitative and quantitative data right? But in this experiment, I don't know if we have any of the qualitative data. Is there any?

3) For presenting raw data, I have to identify the outliers. How do I do that? Do I just say oh, it's 25.5 when it should be 25, so it's an outlier? Or do I have more accurate basis to judge whether it is or not? And if I identify the outliers, do I exclude it from the calculation of mean for the processed data?

4) For processing raw data, do I have to show the calculation process?

5) For presenting processed data, since the aim of the lab is to figure out which one is the most accurate, do I have to present the data with both graph and table?

Please help me!

[Keel]

1) I would advise that all the raw data be put into one single table. The uncertainties can be dealt with by either putting it in the header of the column (e.g. +/- 0.5 cm³) or copy and pasted after each value.

2)If there are no obvious qualitative results then you will not be penalized for not stating any.

3)This is interesting. Normally you would do such a thing in the evaluation aspect of the IA (see: ) But since your IA is about uncertainties its hard to say whether it goes in the DCP or the CE. I would say for this particular IA, it would go in the DCP as you are processing the data in order to find the inaccuracy of the equipment not the limitations of your experiment.

4)Yes that is very important, step by step working.

5)The only way you could graph it is if it you took the % different of obtained value to actual value and graphed it. The one with the least % difference is the most accurate.

I'm not quite sure why you are testing for different volumes. To me your variable should be 'equipment' yet you appear to have taken values for different volumes which in its self is a variable. You may want to watch out for that or explain it to us. Could you also explain to us how you carried out the experiment, because I think I am missing something with regards to the random uncertainties.

[YeunJi Lee]

Ah! Sorry I forgot to explain about the volume. I'm measuring 25ml of distilleed water, and I'm just adding extra amount of measured water to weigh each time for different trial. So at the end of the processing, I would end up with 5 trials of weight of 25ml of distilled water.

For the uncertainties, though, I don't think that would work because I planned to put all the information in one table, like in the file attached in this post. (please check) And I was stuck because each of the equipment have different uncertainty. So I don't know where to put this info.

So if I have to put all in one, could you tell me which graph is better and how should I put the uncertainty?

Thank you!!

uncertainty.bmp

[Keel]

What do you use to measure each 25cm³ which you put into the conical flask? That should have an uncertainty too.

[YeunJi Lee]

Yeah that's exactly what im saying

I used graduated cylinder, burette, graduated pipette and volumetric pipette to measure each,

and I need to note those uncertainties, not of the conical flask because that is just used for weighing the water...

[Keel]

Oh right, I see how you have done your experiment. The first thing is to get rid of the 175.433, we do not want to consider the mass of the conical flask. Secondly I think the random uncertainty for the mass should be 0.002 because of the way an electronic scale works, when you tare your scale to 0.000 that has a +/- of 0.001 too so in fact you are taking into account two lots of +/-0.002 errors.

Secondly, you need either a literature value or a reference sample. How are you going to determine which is the most accurate equipment of you have nothing to compare what you have tested to? If you are not provided with a literature value this can be obtained by using the density of distilled water which gives you 25g. But you must explicitly state that this is your literature value.

I would use your second table, but I would not label them as 25, 50, 75 ect. I would simply state 1st try, 2nd try, 3rd try ect. and I would add an average column at the end and average the value for each equipment. That average will have the uncertainty of the equipment you were using. You will then compare the obtained values with the literature value and obtain the answer of which equipment was the most accurate.

For your evaluation you will find out what % of the error in each experiment was due to systematic errors. i.e. do the same as the link I provided above. The only two improvements I can think of at the moment are increase number of trials to reduce the effects of random uncertainties and use larger volumes for the same reason.

[YeunJi Lee]

The table Ive uploaded was for raw data.. so I will do what u have said for processed data

By the way, do I have to include uncertainty in both raw and processed data?

And do I have to include the outlier when calculating the mean?

Thanks a lot for your help

Edited April 22, 2011 by YeunJi Lee

[Keel]

Yes you should include the uncertainties in your raw data. As I've stated above, you probably should just dump it in with the heading e.g. Pipette +/- 0.05 cm³. A good way to proceed is to do all your calculations towards obtaining your answer fist i.e. which equipment is the most accurate and then proceed with doing the errors in your calculation. No, you calculate the mean for each equipment first. So you get a value for each equipment e.g. 25.91, 25.23 ect. and then you compare it with the 25.00 Hope this made sense.