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Deadline for submission is: 31st May 2019
This is an individual assessment and your work must be your own
Do we have big brains?
It has been suggested that humans have anomalously large brains for their body size. We’ll
investigate this idea by studying collections of brain and body mass data for samples of prosimians,
monkeys, apes and a single homosapian.
The first column of each data set is the body mass in grammes and the second column is
the brain mass in grammes. The data files for the different animal groups are:
Prosimians: https://tinyurl.com/ybhnk5jc
Monkeys: https://tinyurl.com/y9vqdnt8
Apes: https://tinyurl.com/ybvhdh2g
Homosapian: https://tinyurl.com/ycjymwun
Previous studies have shown that brain mass (mbrain) and body mass (mbody) are related according
to the power law:
mbrain = γ × (mbody)
(1)
where γ and ψ are estimated from the given data. If you are unfamiliar with power laws you
can find out about them here: https://tinyurl.com/yb29c3br
Assessment Outline
Report your work in a Jupyter notebook (make sure your report includes your name and unumber).
In your Jupyter notebook include a detailed markdown-based description of the
different steps you have taken for each task and the methods you have used. This should
include a description of the functions you are using, equations you employ and the terms in
those equations. Even if you use a dedicated python package to solve specific tasks, you must
describe the equations that package is using and the terms involved (points will be deducted if
you don’t explain your approach in detail).
IMPORTANT: Code comments will not count as part of your description.
If a given task involves a calculation to produce a final answer, ensure you provide a clear
written statement of your result with an appropriate number of significant figures and, where
appropriate, correct units.
You can find guides on markdown formatting here:
https://www.markdownguide.org/basic-syntax
https://paperhive.org/help/markdown
1Assessment Tasks
Complete the following tasks (total of 50 points).
1. Load and combine the prosimian, monkey and ape data sets into a single array (2 pts).
2. Using the combined data, estimate γ (Eqn. 1) and its 95% confidence interval (10 pts).
3. Using the combined data, estimate ψ (Eqn. 1) and its 95% confidence interval (10 pts).
4. Create a plot showing the mbrain (y-axis) and mbody (x-axis) data, with each group (i.e.,
prosimians, monkeys, apes and homosapians) represented by different coloured points
(5 pts).
5. Based on your estimates of γ and ψ, add a best fit line to your plot and include 95%
confidence and prediction intervals for the full range of mbody values (10 pts).
6. Predict with 95% uncertainties the average brain mass corresponding to a body mass of
50 kg (5 pts).
7. Using your determined regression relationship, estimate if the brain size of the 1 homosapian
included in the data set is anomalously large given their body size (5 pts).
8. Discuss if there any potential issues with the data sample that could affect your analysis
(3 pts).
Assessment Submission
Submit your Jupyter notebook file via the class Wattle page with a filename which is “your
u-number.ipynb”.
2
Deadline for submission is: 31st May 2019
This is an individual assessment and your work must be your own
Do we have big brains?
It has been suggested that humans have anomalously large brains for their body size. We’ll
investigate this idea by studying collections of brain and body mass data for samples of prosimians,
monkeys, apes and a single homosapian.
The first column of each data set is the body mass in grammes and the second column is
the brain mass in grammes. The data files for the different animal groups are:
Prosimians: https://tinyurl.com/ybhnk5jc
Monkeys: https://tinyurl.com/y9vqdnt8
Apes: https://tinyurl.com/ybvhdh2g
Homosapian: https://tinyurl.com/ycjymwun
Previous studies have shown that brain mass (mbrain) and body mass (mbody) are related according
to the power law:
mbrain = γ × (mbody)
(1)
where γ and ψ are estimated from the given data. If you are unfamiliar with power laws you
can find out about them here: https://tinyurl.com/yb29c3br
Assessment Outline
Report your work in a Jupyter notebook (make sure your report includes your name and unumber).
In your Jupyter notebook include a detailed markdown-based description of the
different steps you have taken for each task and the methods you have used. This should
include a description of the functions you are using, equations you employ and the terms in
those equations. Even if you use a dedicated python package to solve specific tasks, you must
describe the equations that package is using and the terms involved (points will be deducted if
you don’t explain your approach in detail).
IMPORTANT: Code comments will not count as part of your description.
If a given task involves a calculation to produce a final answer, ensure you provide a clear
written statement of your result with an appropriate number of significant figures and, where
appropriate, correct units.
You can find guides on markdown formatting here:
https://www.markdownguide.org/basic-syntax
https://paperhive.org/help/markdown
1Assessment Tasks
Complete the following tasks (total of 50 points).
1. Load and combine the prosimian, monkey and ape data sets into a single array (2 pts).
2. Using the combined data, estimate γ (Eqn. 1) and its 95% confidence interval (10 pts).
3. Using the combined data, estimate ψ (Eqn. 1) and its 95% confidence interval (10 pts).
4. Create a plot showing the mbrain (y-axis) and mbody (x-axis) data, with each group (i.e.,
prosimians, monkeys, apes and homosapians) represented by different coloured points
(5 pts).
5. Based on your estimates of γ and ψ, add a best fit line to your plot and include 95%
confidence and prediction intervals for the full range of mbody values (10 pts).
6. Predict with 95% uncertainties the average brain mass corresponding to a body mass of
50 kg (5 pts).
7. Using your determined regression relationship, estimate if the brain size of the 1 homosapian
included in the data set is anomalously large given their body size (5 pts).
8. Discuss if there any potential issues with the data sample that could affect your analysis
(3 pts).
Assessment Submission
Submit your Jupyter notebook file via the class Wattle page with a filename which is “your
u-number.ipynb”.
2