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r Python代写-MTHM504
时间：2022-07-02
MSc Applied Data Science and
Statistics
MTHM504 Thesis project kick off
Tuesday 10th May
SWIOT Building, 9:35 - 11:25
Welcome
Your summer 2022 preferences:
Thesis Projects
• ELE project page: on MTHM504
• Wide range of data science projects, focussed on data
science work, research analysis and careers.
• Start: w/c 9th May 22
• Thesis checkpoint: w/c 6th June: thesis work engagement,
outline, research questions, present lit review, EDA (10%)
• Submit Thesis (70%): 24th August 2022
• Submit Narrated PowerPoint (20%): 24th August 2022
Projects – Thesis
• The report should be written concisely and explain the
topic and context of your project.
• It should provide details of the data and methodology you use and
your results
• You should present a discussion of the main findings, highlighting
any original aspects of the work and/or new findings.
• The written report should be between 30 and 40 pages in
length (as an indication this should be between 10,000 to
15,000 words) including figures, tables and references.
• Computer code should not appear in the main body of the
report.
Projects – Appendix
• You may put additional material in an appendix.
• This might include tables and graphs if there too many to fit into the
main body of the report (you might want to consider limiting the
number in the main body of the report to around 10), but these must
be clearly signposted/referenced within the main body of the report.
• You may also include detailed calculations, statistical
analysis and computer code
• all significant code written as part of the project should be included
within the appendix with detailed comments so that examiners can
easily follow the structure.
Projects – Structure
• Presentation, formatting and logical flow (10%)
• Your report should be presented in a clear and logical manner, with
a clear narrative throughout. You should ensure that figure and
table captions are clear and explanatory and that the content
within figures is large enough to read.
• Introduction, aims, background to the subject (10%)
• What are the main aims and objectives of the project? Is it to prove
a result, test a hypothesis, or develop techniques to solve a
particular problem? If developing a model, what are the key
assumptions/limitations?
Projects – Structure
• Detailed review of literature on which project is based,
description of methodology, underlying theory, etc. (35%)
• Provide details of previous attempts to look at this question -who
has previously written about this subject, what data and methods
did they use, what were their conclusions?. This should include a
discussion of how do the assumptions/methods used in article X
compare to those used in article Y?
• Description of data, analyses and results (35%)
• Where does you data come from? To include initial summaries and
initial data analyses. Application of your chosen methodology to
your chosen data. Presentation and description of results. How
sensitive are your results to the method used /assumptions made?
How do your results relate to those in the literature, which may use
different methods? How would you extend your project given more
time?
Projects – Structure
• Summary and discussion (10%)
• A summary of what you have done and a discussion of the results
you have found, putting them into the wider context of the aims
of the project. What further research do you think is needed?,
e.g. additional data, methodological developments.
Academic honesty
• Academic honesty means always giving full credit for any
other people's contributions to our own achievements (i.e. by
full and correct referencing) and never falsifying the results
of any research. information for students
• All written work, and research carried out must be your own
(taking into account assistance from the project supervisor).
• All literature and sources used must be cited appropriately.
• This includes any code /packages developed by others that you have
used.
o In summary: Today 9:35 - 11:25
o Kickoff & (shortly) a re-cap on report writing
o Form into project theme groups
o Climate analyses and Emergency : John
o Medical analyses : Mark
o Air Pollution: Gavin and Dorka
o Climate and methods: Stefan and James
o Others: join above and discuss
Statistics
MTHM504 Thesis project kick off
Tuesday 10th May
SWIOT Building, 9:35 - 11:25
Welcome
Your summer 2022 preferences:
Thesis Projects
• ELE project page: on MTHM504
• Wide range of data science projects, focussed on data
science work, research analysis and careers.
• Start: w/c 9th May 22
• Thesis checkpoint: w/c 6th June: thesis work engagement,
outline, research questions, present lit review, EDA (10%)
• Submit Thesis (70%): 24th August 2022
• Submit Narrated PowerPoint (20%): 24th August 2022
Projects – Thesis
• The report should be written concisely and explain the
topic and context of your project.
• It should provide details of the data and methodology you use and
your results
• You should present a discussion of the main findings, highlighting
any original aspects of the work and/or new findings.
• The written report should be between 30 and 40 pages in
length (as an indication this should be between 10,000 to
15,000 words) including figures, tables and references.
• Computer code should not appear in the main body of the
report.
Projects – Appendix
• You may put additional material in an appendix.
• This might include tables and graphs if there too many to fit into the
main body of the report (you might want to consider limiting the
number in the main body of the report to around 10), but these must
be clearly signposted/referenced within the main body of the report.
• You may also include detailed calculations, statistical
analysis and computer code
• all significant code written as part of the project should be included
within the appendix with detailed comments so that examiners can
easily follow the structure.
Projects – Structure
• Presentation, formatting and logical flow (10%)
• Your report should be presented in a clear and logical manner, with
a clear narrative throughout. You should ensure that figure and
table captions are clear and explanatory and that the content
within figures is large enough to read.
• Introduction, aims, background to the subject (10%)
• What are the main aims and objectives of the project? Is it to prove
a result, test a hypothesis, or develop techniques to solve a
particular problem? If developing a model, what are the key
assumptions/limitations?
Projects – Structure
• Detailed review of literature on which project is based,
description of methodology, underlying theory, etc. (35%)
• Provide details of previous attempts to look at this question -who
has previously written about this subject, what data and methods
did they use, what were their conclusions?. This should include a
discussion of how do the assumptions/methods used in article X
compare to those used in article Y?
• Description of data, analyses and results (35%)
• Where does you data come from? To include initial summaries and
initial data analyses. Application of your chosen methodology to
your chosen data. Presentation and description of results. How
sensitive are your results to the method used /assumptions made?
How do your results relate to those in the literature, which may use
different methods? How would you extend your project given more
time?
Projects – Structure
• Summary and discussion (10%)
• A summary of what you have done and a discussion of the results
you have found, putting them into the wider context of the aims
of the project. What further research do you think is needed?,
e.g. additional data, methodological developments.
Academic honesty
• Academic honesty means always giving full credit for any
other people's contributions to our own achievements (i.e. by
full and correct referencing) and never falsifying the results
of any research. information for students
• All written work, and research carried out must be your own
(taking into account assistance from the project supervisor).
• All literature and sources used must be cited appropriately.
• This includes any code /packages developed by others that you have
used.
o In summary: Today 9:35 - 11:25
o Kickoff & (shortly) a re-cap on report writing
o Form into project theme groups
o Climate analyses and Emergency : John
o Medical analyses : Mark
o Air Pollution: Gavin and Dorka
o Climate and methods: Stefan and James
o Others: join above and discuss
