Data+Collection+and+Processing

IAs - Design - Data Collection and Processing - Conclusion and Evaluation

Internal Assessment - Data Collection and Processing
This section of your report is the easiest to obtain a complete on and also the easiest to make mistakes on if you are not careful.


 * ** Levels/marks ** || ** Aspect 1 ** || ** Aspect 2 ** || ** Aspect 3 ** ||
 * ^  || ** Recording raw data ** || ** Processing raw data ** || ** Presenting processed data ** ||
 * Complete/2 || Records appropriate quantitative and associated qualitative raw data, including units and uncertainties where relevant. || Processes the quantitative raw data correctly. || Presents processed data appropriately and, where relevant, includes errors and uncertainties. ||
 * Partial/1 || Records appropriate quantitative and associated qualitative raw data, but with some mistakes or omissions. || Processes quantitative raw data, but with some mistakes and/or omissions. || Presents processed data appropriately, but with some mistakes and/or omissions. ||
 * Not at all/0 || Does not record any appropriate quantitative raw data or raw data is incomprehensible. || No processing of quantitative raw data is carried out or major mistakes are made in processing. || Presents processed data inappropriately or incomprehensibly. ||

The easiest way to broach this section is to address each aspect individually. The notes notes below are separated into sections to match each aspect.

[|i-Biology] has produced [|an excellent spreadsheet] with ready made resources to make your data processing a much easier and less time consuming process.

This simple graphing template spreadsheet you may find helpful in processing and presenting data. Read or review the advice below and the guidance. If a template suits your needs make sure you take note of the guidance and then adapt it to suit your needs. media type="custom" key="23698626" //This spreadsheet is can also be used with open office (checked with version 3.3.0)//


 * Recording Raw Data (aspect 1)**

Include all results and observations you made during the experiment. Where at all possible the data recorded should be collected by YOU. If data collected data as part of a group effort you must:
 * 1) Be very clear which data is yours and which came from another student
 * 2) Never accept data in the form of a table - this would be regarded as plagiarism and/or collusion

Further information on this point can be found [|here]

The table should have a full title that makes the reader understand the results without even needing to read the whole lab report.

Titles, units and uncertainties for the columns need to be displayed in the table and should be shown clearly.

The results should be related to the aim and the hypothesis. So if you are testing the effect of temperature on enzyme activity the table of results will have the first column showing a range of temperatures and the second column will have the rate of reaction, which could be recorded in different ways: for example the volume of gas produced, color change, mass of a product or a reactant, depending on the type of experiment.

Decimal points consistent with precision of the measuring equipment and constant for each variable.

Qualitative data, i.e. what you noticed but could not measure, should be included. It demonstrates that you were not doing the experiment blindly, but evaluating through the whole process. You will also gain insights to help with your evaluation at this point too.


 * Processing Data (aspect 2)**

In Biology a form of processing such as % change (in mass/volume/length) or reaction rate (1/time) should also be done, if appropriate. A great resource is this [|Excel spreadsheet] from [|i-Biology] which helps you choose the appropriate form of data processing.

Adjust the precision to reflect processing (if needed) guidance is given below. If you are using a reaction rate or % change calculation then you lose uncertainty at this step. See the presentation for guidance: media type="custom" key="23698628"

Next you should always aim to calculate the mean and standard deviation. This is your most basic kind of data processing.

In some investigations you will be looking for patterns (i.e. 5 x 5 minimum), drawing a curve of best-fit and judging the strength of the correlation. In others you will be looking for significant differences between two (or more) mean values (minimum 10 values per mean). If you are looking for significant difference between the means then consider carrying out a t-test at this point. Review 1. Statistics, or [|excel t-tests from click4biology] if you are unsure how to do this.

Always state how you carried out the processing by including the formula used (and/or the excel functions used). Giving example calculations as well a quoting the formula is advised.

N.B. the AVERAGE function in MS Excel is in fact a calculation of the mean and should be named MEAN. Don’t make the same mistake as Microsoft.


 * Presenting Data (aspect 3)**

You are presenting processed data, do not graph raw data by mistake. Raw data may additionally be graphed, should only be done if helpful as it will not gain you marks.

Titles self-explanatory, complete and consistent with the processed data.

Axis scaled correctly, you don’t’ have to start at zero, just graph the range of your data

Units and uncertainties included on the axis labels. Decimal places must be consistent with processed data

Error bars should be included and do not forget to state the source, e.g. an annotation under the graph. Refer to the statistics topic to review how this is done.

Graph should almost always be a line graph (in MS Excel this is referred to as a scatter graph – stay away from their line graphs). Sometime a bar chart will be appropriate, but this is rare as most IAs will be looking for a trend/pattern.

A curve (which may be a straight line in some circumstances) of best fit should be drawn, do not simply join the points unless the fit is perfect. Remember a good curve will go through the error bars (wherever possible) and the curve will go through the middle of the points. The errors (gaps from mean to the curve of best fit) above the curve should equal the errors below the curve.

Avoid using Excel’s trend fitting tools unless you understand the underlying maths, it’s easy to make a poor choice of algorithm. A better practise is to draw by hand or using a shape (e.g. curve/arc) or line that you adjust manually. Instructions on how to do this can be found below: media type="custom" key="23698630"

Open Office users can find their instructions here: media type="custom" key="23698632"

Graphs should eventually occupy at least ½ a report page, a whole page is better