Unit 3: Investigative Biology
Key Area 3: Reporting and Critical Evaluation of Biological Research
Key Area 3: Reporting and Critical Evaluation of Biological Research
a) Background Information
Scientific reports should contain:
Title
Should provide a succinct explanation of the investigation and include the independent and dependent variables. It should also include the organism/system/molecule being studied.
Examples
Abstract
The abstract (or summary) outlines the main aims and findings of the investigation. The abstract summarises how each variable has been altered/measured and the main effect that altering the independent variable has had on the dependent variable.
Aim
There will be at least one aim in an investigation, but often more. An aim must link the independent and dependent variables.
Read the following aims and identify which you think would gain the mark.
Background information
Background information should be clear, relevant and unambiguous.
A title should provide a succinct explanation of the study.
An abstract should outline the aims and findings of the study.
An aim MUST link the independent and dependent variables.
Background information
The introduction should provide any information required to support the choices of method, results, and discussion. An introduction should explain why the study has been carried out and place the study in the context of existing understanding. Key points should be summarised and supporting and contradictory information identified. Several sources should be selected to support statements, and citations and references should be in a standard form. Decisions regarding basic selection of study methods and organisms should be covered, as should the aims and hypotheses.
Hypothes(es)
The introduction should include at least one hypothesis. This is a prediction for the outcome of the investigation if a certain theory were true. The hypothesis is the statement that the investigation is designed to test.
Citations and references
When writing your introduction you will most likely use textbooks and webpages to do so. You must give the writers of these works credit for their information to show it is not your own work but that you have got the information from elsewhere.
We do this by citing and referencing the information.
Sloths on Wikipedia
Citations and references
Harvard Method
The works cited in the running texts are identified by the name of the author(s) and the year of publication.
Example:
“Smith (2009) presents convincing evidence that global warming is a much bigger threat than previous research has assumed (Johnson 2005; Abugabar and Jelan 2006; Sesalem et al. 2012; Leery 2010a,b).”
Citations and references
Vancouver Method
Each piece of work cited within the text is identified by a unique number. If a piece of work is cited more than once, the same citation number must be used.
Example:
“Smith 3 presents convincing evidence that global warming is a much bigger threat than previous research has assumed 1, 4-7, 9.
b) Reporting and evaluating experimental design
A method section should contain sufficient information to allow another investigator to repeat the work. The experimental design should address the intended aim and test the hypothesis It should allow the treatment effects to be compared to controls.
Any confounding variables should be taken into account or standardised across the treatments.
The validity of an experiment may be compromised when factors other than the independent variable influence the value of the dependent variable. The validity and reliability of the experimental design should be evaluated. An experimental design that does not address the intended aim or test the hypothesis is invalid.
Method - controls
Reminder
Negative control: Provides results in the absence of treatment.
Positive control: A treatment that is included to check that the system can detect a positive result when it occurs.
Selection Bias
The selection of a sample in a non-random way, so that the sample is not representative of the whole population.
Sometimes selection bias may have prevented a representative sample being selected. Also sample size may not be sufficient to decide without bias whether the change to the independent variable has caused an effect in the dependent variable.
Selection Bias therefore affects validity and reliability.
Inadequate sample size
Sample size may not be sufficient to decide without bias whether the change to the independent variable has caused an effect on the dependent variable.
Inadequate sample size means the sample may not be representative of the whole population. It therefore affects validity and reliability.
c) Data Analysis
Once raw data is collected you are expected to process the information to interpret what it means. This includes (as appropriate) graphs, mean, median, mode, standard deviation and range. The data should be presented in a clear, logical manner suitable for analysis.
Analysed data will be presented in the results section of your report.
Variation and reliability
It can be useful to measure the variability:
1. Between individual replicates of a data set.
2. Between independent replicates of an experiment/study.
Measurement of variability within and between data sets can inform about reliability.
Standard deviation (SD) and variability about the mean of a data set
Standard deviation (SD) is one way of telling how much each measurement of a data set differs from the mean of the data set.
The greater the SD of a data set, the more variable the data (and the less reliable).
Other measures of variation about the mean (aside from SD) include:
Error bars
Error bars are used to represent measures of variation about the mean (e.g. SD) on a graph. Examples of line and bar graphs with error bars are shown below:
Error bars and variation
Smaller error bars indicate less variable data and therefore a more reliable data set.
Larger error bars indicate more variable data and therefore a less reliable dataset.
Error bars and significant difference
Often studies will involve several sets of data and looking to see if they are different. A typical scenario would be to compare treatment groups with a control group.
Error bars and significant difference
Statistical tests are used to determine whether the
differences between the means are likely or unlikely to have occurred by chance.
Interpreting error bars can give an indication of whether or not a difference is more or less likely to be significant.
Error bars and significant difference
Data Analysis
A statistically significant result is one that is unlikely to be due to chance alone. If the treatment mean differs from the control mean sufficiently for their error bars not to overlap, this indicates that the difference may be significant.
Finally consideration should be given to the validity of outliers and anomalous results.
d) Evaluating results and conclusions
The final section of a scientific report is evaluation of the results and conclusions.
Conclusions should always refer to the aim, the results and the hypothesis.
The validity and reliability of the experimental design should be taken into account and discussed. Consideration should be given as to whether the results can be attributed to simply correlation or causation
d) Evaluating results and conclusions
Evaluation of conclusions should also refer to existing knowledge and the results of other investigations.
Scientific writing should reveal an awareness of the contribution of scientific research to increasing scientific knowledge and to the social, economic and industrial life of the community