Chapter 7. MDP discussion, final presentations, and final project reports

MDP program

• Modelling, Data

and Predictions

• Designed to be completed

in 16 months

• Data science related careers

in industry and government

• Mentorship
• PD workshops
• Internship
• Capstone project

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Final Project

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• Answer the given questions and then go Beyond them
• Show what you learned in class
• Please do NOT use any AI tools!

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Report due in class on December 8:

• No length limitation but preferred to be within 10-30 pages
• No font size limitation but suggested to be 12 pt Times New Roman
• Use Latex or Word to write the report and then generate PDF

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Final project report

A project report should consist of the following components:

• Title
• Abstract
• Introduction. Include background, description/graphs of available data, problem description, questions to be addressed. Use non-technical terms.
• Formulation of the mathematical model. List variables/parameters, assumptions, restrictions, and justify the development of the equations.
• Solution of the problem. Outline of the mathematical methods used to solve the model. Details such as complicated computations or numerical code should be provided in appendices.
• Interpretation of results. Answer the questions posed in the introduction, summarize major findings. Use non-technical terms.
• Critique of the model (Discussion). Does the model satisfactorily answer the questions posed? Discuss the limitations of the model, possibilities to improve the model, etc. Think ahead, what would you like to do if you had more time.
• References
• Appendices with supporting materials. Include a copy of any code used, details of calculations, etc.

Four (Easy) Steps to Better Writing�Paul Dudenhefer, Duke University

• PRINCIPLE 1: Keep your complete grammatical subjects short.
• Long subject: A full explanation of why the model cannot accommodate this particular case of omitted variable bias is given in the appendix.
• Short subject: The appendix explains in full why the model cannot accommodate this particular case of omitted variable bias.
• PRINCIPLE 2: Express key actions as verbs, not as nouns.
• We conducted a review of the matter.
• We reviewed the matter.
• PRINCIPLE 3: Begin sentences with “old” information.
• PRINCIPLE 4: End sentences with new information.

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If you want to learn more, please read “Style: Ten Lessons in Clarity and Grace” by Joseph M. Williams

Final presentation

• Read Sample of final presentation on the course website
• Read the project guidelines

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REQUIREMENTS FOR THE PROJECT PRESENTATION (10 mins + 1 min)

• Statement of the problem. What are the questions to be answered? Use plain language, non-technical terms. Give some background.
• Description of the model. What are the major assumptions? How is the problem translated into equations?
• Outline of the mathematical and numerical methods used to solve the model. Give enough details to demonstrate to the audience that you know what you are doing, but not so much to put the audience to sleep!
• Interpretation of the results. Use plain language, non-technical terms. Make sure that the questions posed at the beginning have been answered. Give some intuition as to why your solution is correct. Discuss the limitations of your solution, possible improvements to the model.

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• To make effective use of time and your audience's attention, make use of pictures (graphs, schematics, flow diagrams) as much as you can (a picture is worth a hundred words!).

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• Presentations should be prepared in electronic format (powerpoint file or pdf file) and sent to Jacob Serpico serpico@ualberta.ca at least 15 hours in advance (before 9:30pm in the previous day).

Rubrics of the final presentation (totally 10 pts)

• (2 pts) Statement of the problem.
• (2 pts) Description of the model.
• (1 pts) Appropriateness of the model.
• (2 pts) Explanation of the mathematical and numerical methods used to solve the model.
• (2 pts) Interpretation of the results.
• (1 pts) Overall clarity of the presentation.

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Your presentations should have …

• Setting

the scientific and/or historical context of your topic

• Plot

structure of the story, from the statement of a problem/objective to the conclusion and take-home message

• Characters

variables, equations, objects, etc.

The Setting�(scientific and/or historical context)

Questions to think of when you set the stage for your presentation:

• What motivates my research? Why am I doing this?
• What is the significance of my results? Why should anyone else care?
• Who else has done related work? How does my research relate to published works? How does my work fit in with others?

The Plot�(from problem statement to conclusion)

• In broad terms, what is your question of interest?
• Is your research about developing a better algorithm to accomplish a specific task?
• Are you investigating a conjecture?
• Have you developed a new counterexample?
• Have you established a proof?
• Are you developing a new model to describe a certain (natural) phenomenon?
• What is the specific question(s) you are addressing and what are your conclusions?

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The Characters

• Characters are the mathematical objects that play a role in your story:
• Variables, equations, groups, operators, named conjectures or theorems, function spaces, algorithms, models, techniques, …
• All characters must be introduced (some with more care than others)

Signposting: Giving Structure to Your Presentation

• Signposts are aids that let the listener know where you are in the story and when you’re moving to a new stage in your presentation.
• Signposts can take many different forms: outlines, questions and answers, partial summaries, “where next” type comments, etc.

Image source: www.vanderbilt.edu/HRS/guide/contract/stII2.htm

Find the Signpost …

Eliminating Unnecessary Detail

• Resist the temptation to tell the audience everything you know about the subject.
• Don’t bury the key points in detailed descriptions of methods or proofs.

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What is the point of this talk?

Scientists Must Speak, page 7.

This is Not a Good Idea!

Credit: Sam Gross, The New Yorker

Graphs, Charts, and Tables

• Label all your axes.
• Describe the axes verbally as well.
• Discuss the interesting features of the graph: what can we conclude from the graph?

Use Color Effectively

Can or Should I Read My Slides?

• Preferably not.
• If you really must, then at least have the text in point form.
• Give the audience time to absorb the information in each point.
• Explain details verbally instead of writing dense text on slides.

Maintaining the Audience’s Attention

• You need a “hook” to capture your listener’s attention right from the start.
• Properly introduce all characters (review definitions if needed).
• Periodically remind the audience of the objective and conclusion of the research.
• Provide a succinct but strong take-home message.

Scientists Must Speak, page 9.

Schedule of final presentation speakers

November 19: Spencer Olson, Yajing Ban, Alexander Shulhan, Mostafa Khosravi, Alan Fang, Tristin Schlauch, Harry Xing.

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November 24: Natalie Boston, Haiying Kuang, Jake Gannon, Asma Mushtaq, Xindi Li, Michael Akoto, Ben Brunham.

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November 26: Namreen, Qiyuan Zhang, Muniratu Tahiru, Gabriel Okoli, Vaibhavi Joshi, Aileen Chen, Suyu Wang.

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December 1: Yewei Wang, Mohammed Uddin, Masum Shamim, Zixiu Ouyang, Amna Ihsan, Saif Mohammed, Ray Hasan.

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December 3: Jaskaran Attal, Mohammed Hamzah, Gui Kang Ow Yong, Krati Varshney, Fadil Mohammed, Mounika Nallabothula, Parshva Shah.

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December 8: Chaya Komarthy, Vincent Adetula, Henry Antwi, Deckar Hoang, Mohamed Omar. (Final Project Report due in class)

Final project report is due on December 8 in class!�Please submit one printed document.