Apparatus list
Table to show reasons for choice of apparatus
Safety
Table to show how concentrations of working solutions will be made
Table to show the variables that must be controlled
Class practicals and individual preliminary work can help you to:
- identify key variables and design ‘fair test’
- plan a procedure which includes appropriate controls
- select equipment
- work out a suitable number of measurements / observations to include in plan
- work out a suitable range of measurements to take.
Reasons for choice of equipment can be based on the preliminary study once you have used the apparatus and seen its advantages / disadvantages.
The justification of your choice can follow more easily after a thorough preliminary study.
Advice on Implementation
Some common errors when recording your data -
- Not recording all the raw data
- Constructing tables that do not include all the relevant information
- Using two or three small tables when one table (often ‘landscape’) is required
- Using a separate table for mean results when these should be in the last column of a results table
- Not giving units at the head of the columns / beginning of the rows
- Putting units in the body of the table
- Not following IoB guidelines on construction of tables.
Institute of Biology Guidelines:
- Axis labelled
- Informative title
- Line through the points (and line of best fit)
Advice on Analysis
It is important that you engage with the data that you have collected. All aspects of data processing need to be assessed:
- How much data has been collected?
- Is it possible to carry out a statistical analysis on the data?
- How has the data been processed?
- Have anomalous results been identified?
- Is it possible to draw a line of best fit with confidence?
- Does the data support the prediction?
- Is it possible to write a description of what the data shows making use of the figures / datum points to illustrate trends?
You should use the science underpinning the investigation to explain the results that you have collected and the trend(s) that you have identified.
In other words…
- What trend(s) can you see in the data?
- Describe the trend in words.
- Include figures from tables and graphs in your description.
- Give a simple explanation of the trend in terms of your knowledge.
- Carry out some mathematical processing of the data.
- Make sure that the processing is appropriate.
Advice on Evaluation
Many of you forget that you are evaluating the data that has been collected as well as your procedure. In the evaluation you should
- identify sources of error
- quantify sources of error
- identify major sources of error
- describe the effect of these errors on the results
- suggest improvements
Try using a table like this to clarify your ideas;
Data
There are various ways in which this can be approached
-
identifying anomalous results in raw data by circling, underlining or highlighting in tables
- identifying anomalous results in processed data by circling means in tables or on graphs – these are anomalous results that do not fit the overall trend
- showing the range of results about the mean
- calculating the standard deviation for the replicate results
- calculating the 95% confidence interval, which is better for comparing different sets of data than standard deviation.
We hope that this goes some way in helping you with your write-up. There is one final golden rule
Quality is better than quantity!
