联系我们： 手动添加方式: 微信>添加朋友>企业微信联系人>13262280223 或者 QQ: 1483266981

BIOL0001 Data Interpretation Exercise Instructions 2022-2023
The purpose of the Data Interpretation Exercise is to test your application of the statistical
methods that you have learnt throughout the course and continue to develop your scientific
writing.
This year’s project has been developed by Alice Leavey, a PhD candidate in Cell and
Developmental Biology. In brief, Alice is interested in investigating how skeletal variation
between species predicts their locomotion strategy. Alice provided a recorded presentation
on their work followed by an online Question and Answer session (both recordings available
via Lecturecast). She introduced what she studies, the experiments you will be analysing and
an explanation of the dataset. Dr Bellamy gave a follow-up talk giving a general introduction
to the DIE (similar in contents to this document) and outlining the output that you are
required to produce.
The project you will be working on consists of a single large dataset testing a group of
similar and related hypotheses. You will be tasked with independently analysing the data,
without any guidance on which specific tests to use. Your work will be presented in the form
of a scientific paper, although not all the parts of a paper will be required. Specifically, you
have to write 4 sections:
1) Summary of the Statistical Methods (300 words maximum)
2) Results (600 words maximum)
3) Discussion (750 words maximum)
4) References (no word limit)
Figure legends and within text references are included in the word counts. End of text
references do not count towards any word count (a good starting point for your further
reading is the references provided by Alice).
You will produce one document, written in the style of a scientific journal. This means it is
written in continuous prose and not in note form. Different journals have different styles.
You will need to produce your paper in the style of the ‘Journal of Evolutionary Biology’, the
formatting is given below:
Journal of Evolutionary Biology (wiley.com)
The deadline for the exercise is Monday 9th January, 1600 (i.e. the start of term two). The
submission is made via the Turnitin system (on Week 11: Data Interpretation Exercise’ tab).
If you have a SORA or approved EC and wish to submit a week later, a separate submission
link will be added with a deadline of Monday 16
th January, 1600.
What will I need to know
You will need to apply the knowledge of all the statistical methods that you have developed
throughout this course. The datasets involve large sample sizes, it is therefore advised that
the calculations are not done by hand. As such, you would need to use some sort of
statistical software. The statistical tests can all be done on Microsoft Excel, but preferably
the analysis should be performed in R. The latter of these software is far superior in data
analysis and presenting the results of your analysis. You are welcome to apply statistical
tests not explicitly used in the course only if you think they are appropriate.
Details of where to learn about the Project
Alice has produced a word document ‘DIE Project 2022-23’ which introduces her work and
the data sets that you will be analysing. The data you will be analysing is found in the Excel
file ‘DIE Dataset 2022-23’ and is contained within one sheet. Remember that this work is
introduced in the presentation by Alice on Tuesday 13th December.
Details of the DIE Write up
1) Summary of the Statistical Methods
Word Limit: (300 words maximum)
Each hypothesis will need different statistical methods. You will need to summarise the
statistics that you did, which you have done in a previous tutorial. Any changes to the raw
data (such as transformations) would need to be described here. You must be explicit in
saying what you were testing (including the variables) and what statistical test was used.
For example, referring to the statistical correlations of lectures 13 and 14, I might say: “The
effect of inbreeding on male and female eyespan was determined by testing the significance
of the correlation coefficient of the inbreeding coefficient versus the eyespan trait in both
sexes.”
2) Results
Word Limit: (600 words maximum)
The results section of a statistical paper will generally begin with summary statistics such as
means, 95% confidence intervals of the means. It should follow the same structure as the
description of the statistical methods given in the Statistical Methods. It should be
answering the key questions of the paper/section heading. Generally, results sections report
the calculated test value, degrees of freedom and P-value. References to critical values, null
hypotheses and alternative hypotheses are not made here. Some examples are shown
below:
An example of the reporting of a correlation:
“There was no correlation between soil pH and crop yield (r6 = 0.154, P>0.05).”
An example of the reporting of a t-test:
“Plot 1 produced a longer plants than Plot 2 (mean plant height in Plot 1: 5±1cm, mean
plant height in Plot 2 = 3±1cm; t23 = 5.634, P<0.01).” An example of the reporting of an ANOVA: The three plots differed in plant height (F2,45 = 4.356, P<0.001, see Figure 2).” Generally, if there are more than 2 groups, means ± 95% CI are summarised in tables, rather than within the text as they are in the t-test example. Meaningful figures such as scatter graphs, box plots or bar charts should be included in the results section (if you prefer you can list them at the end if it makes formatting simpler). Figures should be numerically numbered and include a figure legend (not title). Where appropriate, this legend (or indeed the graph itself) may include summary statistics. Statistical checks (such as homogeneity of variances or checks of normality) tend not to be given in the results. The only cases where they might be reported is when these are significant (but not always!). Figures showing these statistical checks (such as QQ Plots) would never be shown as figures. Figures are kept to displaying the most important results only. 3) Discussion Word Limit: 750 words maximum The discussion should follow the results section and is found in all scientific papers. The discussion should be written in the style of a Scientific Paper. The structure of discussions can vary, but they can broadly be written as followed: The discussion begins with a summary of the experimental results, beginning with the key findings and interpret what they mean. This means that you will need to explain your results in a scientific context. Do the results follow the predicted pattern/hypotheses You will need to put your results into a broader context and explain how they relate to other findings, which will require you to research the field. It is important to know the limitations of your investigation. It may be that some of your results are not clear or conclusive. But remember: A non-significant result does not mean the result/experiment is wrong! Unexpected or non-significant results still reveal something about the system being studied. Perhaps more importantly, a discussion will give further hypotheses which may follow this current study. An experiment always raises further questions of research that can be followed. It may be the case that there are publications that already answer some of these questions. It is important to know the current state of the literature to suggest future directions. A discussion should end with a clear conclusion of the key findings of the research, and a clear explanation of their relevance and importance. 4) References No word limit You will need to reference any source (other than the lectures) both within the text and at the end. If you use figures or pictures modified from sources, they need to must be referenced. Within text referencing counts towards the word count of that section. The reference style needs to be done in Harvard or Vancouver. There are lots of variations of these referencing styles. It does not exactly matter which formatting variant you use, as long as you are consistent with your format. As an example, see a Harvard formatting below: Within Text referencing: 1. Author: (Author’s last name year), for example: “Students really enjoy BIOL0001 (Murray 2022).” or “Murray (2022) found that students really enjoy BIOL0001.” 2. Authors: (1st Author’s last name & 2nd Author’s last name year), for example: “Students really enjoy BIOL0001 (Murray & Bellamy 2022).” or “Murray & Bellamy (2022) found that students really enjoy BIOL0001.” 3. or more Authors: (1st Author’s last name et al. year), for example: “Students really enjoy BIOL0001 (Murray et al. 2022).” or “Murray et. al (2022) found that students really enjoy BIOL0001.” End of Text referencing: Paper: Authors (Surname, Initial). Year. Title. Journal, Volume, Page Number. For example: Murray G. & L. Bellamy. 2022. Biosciences students really like BIOL0001 Introduction to Genetics. Statistics Teaching Monthly, 4, 1-6. Book: (Authors. Year. Title (you may include chapter). City, Publisher. For example: Murray G. & L. Bellamy. 2022. How not to teach statistics. Murray, London. DIE Writing Workshop As a reminder, we looked at examples of students’ DIE outputs in the DIE Writing Workshop. The outputs of these students are very similar in style to your own output. It is worth reviewing the recording of this session if you missed it. Submission Your report should be submitted via the Turnitin submission on the ‘Week 11’ tab. At the start of the report please give an appropriate title (of your choice), Name, Student Number, and Word count (not including the end of text references). If you so wish, you can include the feedback form, but it is not necessary as we will provide all this feedback when we mark the submission. Plagiarism It is departmental policy to fail anyone caught deliberately plagiarising someone else’s work. Your submission is made via Turnitin which automatically checks your submission against all of the internet. Thus, it is impossible to get away with it! Please make sure that you reference your material. Copying significant proportions of an individual’s work and referencing it is still plagiarism.. Accidental plagiarism does happen, so please make sure that you check your plagiarism score beforehand using the following Moodle site: Plagiarism and academic writing for Students 2022/2023. Remember this is meant to be an independent piece of work. In the 2020-2021 academic year, I had to deal with many cases of academic collusion, plagiarism cases where students worked too closely together. There was evidence that students had collectively decided the best way to analyse the datasets together. As such, most students used the same further test not covered on the course and made the same fundamental errors; they all got no higher than a 2.2. Marking We will have a team of three markers who are responsible for marking this year’s DIE. We aim to complete this within 4 weeks of your deadline. The Course Organisers will also double mark a selection of papers to ensure consistency. The papers will be marked out of 100 using the Faculty of Life Sciences Mark Scheme. Dr Bellamy has uploaded an annotated copy of this mark scheme and it was discussed in the context of this assessment by Dr Bellamy in Lecture 18. Please refresh yourselves with this before beginning the assignment.