Get it right – DCP tips

Octobers blog post focused on getting Design labs right so I thought it would be worth staying with the theme of IA labs and giving some tips / hep on DCP.

There are two ways in which your teacher will give you an IA lab:

(1)  They may ask you to first design a lab and then carry it out and analyse the data. This is the hard way – it can (sometimes) be really hard to produced good IA data from student designed labs. Not because students don’t produce very good work but because the other option (the easier route is based on labs that have been trailed and fine-tuned hundreds of times).

(2) The easier route for DCP is to use a method that the teacher has given you. In other words, the lab has been designed for you. There is nothing wrong with this and it is perfectly acceptable under current IA rules for your teacher to do this. Just make sure the teacher has not told you what data to collect or has included a table of data or a graph with labelled axes for you … This is categorically not allowed!

Aspect 1 of DCP revolves around the collection of raw data. Whenever you carry out an experiment, there will always be two pieces of data to collect:

Quantitative data (think quantities or numbers) – this could be a time, a pH, a mass and so on. It will have a number and probably units as well.

Qualitative data – this is often overlooked but a very important piece of information to collect. Quantitative data will be an observation (for example, it was hot, it went pink, it bubbled, a green ppt. appeared and so on). There are very very few labs that do not have any qualitative data to collect (can you think of any examples?)

If you have only collected one of these pieces of data, the best you can achieve is a ‘p’ for this aspect.

DCP aspect 1 also has other parts to it as well. You are probably going to draw a table to collect your raw data. Don’t forget the heading and units for this table. Each column in the table should also include an uncertainty for the associated piece of apparatus that is being used to collect the data.

DCP aspect 2 is, in my opinion, the easiest part to get right (you may disagree when I tell you why). To achieve a ‘c’ for DCP you need to just correctly process the raw data to get the final answer that you have been asked to find out. Easy? This is where your theory lessons come into play and you can expect to do some number crunching (use a calculator) as well as your class notes / text book for this aspect.

Finally, we move onto DCP aspect 3. This aspect assesses your ability to correctly process and present your final answer.

Errors and uncertainties need to be calculated first as a % uncertainty, then added together to provide an overall uncertainty and then finally converted to give an absolute value. For example, you may have worked out an enthalpy to be -14,630 J + / – 34% but please convert your 34% into a kJ mol -1 value (in other words, what is 34% of 14,630?)

The final answer also needs to be carefully presented. Look at the data you have used to achieve your final answer. The final answer should be quoted to the smallest number of significant figures as you used in your calculation.

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For example, to get -14,630 J you had a mass of 100.0, a specific heat capacity of 4.18 and a temperature rise of 35oC. Technically, this value should be presented as -15,000 J so that it is consistent with the smallest number of significant figures that has been used in the calculation (the temperature change is the smallest, to 2 significant figures and -15,000 J is to two significant figures).

It can take time getting used to this but with practice you will get there!

Good luck and if you have any questions, I would love to hear from you.

2 Comments
  • Moushumi Mandal
    April 28, 2014

    Hi David,
    Thanks. I wanted to clarify that when we write the final answer(experimentally obtained value)only then we take care of the sig figs and accordingly that of the uncertainty too. Am i right?

    Thanks

  • David Allen
    May 5, 2014

    Hi Moushumi,

    That sounds correct to me!

    Good luck.

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