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日期：2022-12-03 12:27

Final Data Analysis Report

Due: December 20, 2022 by 11:59PM ET on Quercus

No late submissions will be accepted

Goal of the Assessment:

Part 3 of the Final Project is your opportunity to demonstrate all that you have learned

throughout the course. This will be done by showing the teaching team that you can use the

methods and techniques learned in the course appropriately. You can use the feedback that

you have received in Part 1 and 2, as well as in the video project to write a report that is in a

common research paper format (IMRD: Introduction, Methods, Results, Discussion). Writing

these kinds of reports is likely something that, as a graduate student or a statistician working in

industry, you will find yourself doing occasionally.

Since this assignment is used to assess how familiar you are with the use of the tools and

methods from this course only, you should NOT use materials that were not covered in this

course. Instead, focus on showing us how much you know about everything we have discussed

throughout the term.

It can also be used as part of a dossier when applying to jobs to showcase your abilities as a

statistician and data analyst.

General Instructions:

Using only methods and techniques presented in the lecture slides throughout the term, you

are tasked with answering your proposed research question by creating the ‘best’ linear

regression model that meets the requirements of your research question. You will then need to

write a report (details below) that (i) introduces your research question and presents some

background, (ii) outlines the steps in your analysis that you followed to reach the ‘best’ model,

(iii) presents the results of your analysis and describes and justifies the decisions you made, and

finally (iv) discusses the final model, its interpretation and its limitations in terms of its ability to

meet your research goals. It should be made clear whether you are aiming for a model that

makes good predictions, or a model that is more descriptive and easier to interpret, or some

combination of both.

The feedback and work you have put into Part 1 of the final project should help you structure

your report in a professional and easy-to-read fashion, as well as provide you with a good

beginning to your introduction section. You may want to consider adding some additional

background research or more discussion about how your research question is important and

different from the background you present. The EDA portion of part 1 should be helpful in

writing the beginning of the results section, where you display the characteristics of the data

you will use to answer your question.

The feedback and work you have put into Part 2 of the final project should help you structure

the methods section of your report, where you will outline the process you followed/tools and

methods you used to answer your research question. The feedback should also help you with

how you approach your data analysis itself.

How to present your final report:

Once you have decided upon the ‘best’ model to fulfill the goal of the project, you must write

up a short scientific report. There should be 4 main sections of your report:

Introduction section: where you introduce the purpose and relevance/importance of

the project and provide some relevant background information on the topic (no results

or data should be presented here).

Methods section: where you describe and explain the methods, tools and techniques

used to arrive at your final model (no results or data should be presented here, but you

can tell us where you found your data and what variables it contains).

Results section: where you present a numerical/graphical description of your study

sample and important results that led you to make crucial decisions in building your

model (following the methods you outline in the earlier section), followed by the final

model and any other important results

Discussion section: where you interpret your final model and describe why it answers

the research question and why it is important, as well as discuss any limitations that still

exist based on your results.

You may use tables and plots to help present your results, but they must be relevant and well-

thought-out to convey as much information as possible without being too overwhelming or

confusing. When explaining your methods, try to avoid just stating that you used a specific

method, but add an explanation for how it is used to achieve a specific task. When presenting

your results, avoid repeating exactly what you wrote in your methods section. Instead, focus on

the results of the process you described earlier, and use numerical values/graphical results to

support the decisions you made in arriving at your final model. See the rubric for more

information regarding the various report components.

If you want more information about how to structure your report and what should be

contained in each section, see this cheat sheet and this outline for reports (you may ignore the

abstract portion since you do not need one). Note that not all the elements in these resources

need to be included in your report. But you can use these to better understand how to

structure your submission.

Finally, if you use any external resources outside of the lecture slides, e.g. to provide

background on your topic, you should include a reference section at the end of your report. You

may follow APA citation styles to help format your references. For some resources on how to

cite, see the library page on citations.

What to do if you want to change your dataset or research question:

If you wish to change your dataset or research question from what was originally proposed in

Part 1, you are allowed to do so. However, you will need to provide a written statement that

proposes the change you wish to make. In order to change your dataset or research question,

you will need to submit a 1-page document (to be submitted by December 4 at 11:59PM ET on

Quercus) that answers the following two questions:

1. Why are you changing your topic or dataset? Elaborate on what made your original

dataset or topic not appropriate for the final project.

2. What makes your new topic and/or dataset more appropriate than the previous one?

Be sure to clearly state your new research question and provide a short, written

description of where you located your dataset and what information it contains.

The instructor will then approve or provide suggestions to improve your new dataset/research

question.

Technical Requirements of the Final Report:

Your report should be typed using whatever software you prefer but must be saved and

submitted as a PDF or .docx file on Quercus. Your report must meet the following

requirements:

Font: 12-point font in a style similar to Times New Roman (this is the default in R

Markdown)

Spacing: single-spaced

Word count: up to a maximum of 1500 words in total (this does not include captions on

figures and tables, however, you should also not make captions excessively long or

contain information that isn’t mentioned in the main text). We will still accept a report

that exceeds the word limit by no more than 150 words.

Number of tables/figures in the main report: 5 in total, but you may use any

combination of tables and figures

Figures and table captions: all figures and tables included should include a caption that

describes what is being presented (caption not included in the word count).

o Captions should not contain information that is not also discussed in the main

report

Figure properties:

o All plots should have an appropriate title and axis labels, avoiding the use of

variable names as they appear in the dataset

o A figure may include multiple individual plots but they should be related to each

other and make sense as to why they are being presented together

§ Avoid having too many plots in the same figure to ensure that they are

legible and clear.

Reference list or bibliography at the end of the report (will not count towards word

count), using appropriate citation style

Appendix: you may add an appendix at the end of your report to include some

additional tables or figures that were not important enough to be part of the main

report, but still relevant to your analysis:

o up to 3 additional tables/figures but they should only be included if they are

relevant to the analysis and are referred to in the main text.

R code: In a separate file (i.e. RMD file), you should upload your cleaned and complete

version of the R code that was used to conduct your analysis. The R code should be well-

organized and commented appropriately to indicate what each line/section of code is

doing.

Checklist for submitting final project part 3:

1. Your final written report which follows the requirements above.

2. Your R code that shows your complete analysis (this will be used to verify the results

displayed in your written report and will not be assessed for content).

Things to keep in mind while writing your final report:

o You do not need to write out the results of every step you took in your analysis as this

will make your report too long.

o Instead, focus on summarizing the most important results, especially where a big

decision was made. You need to justify it any big decisions.

o For the rest of your results, very short mentions of the process with a brief piece

of evidence provided are enough to allow your reader to follow your analysis and

understand how you arrived at the final model.

o Rather than presenting the results of each step separately (e.g creating separate tables

for each), consider putting together one larger table that you can refer to in your

discussion of many steps in your analysis so that you don’t use too much space

o For example, if you are selecting between a few different models, you could

consider presenting a table that includes many different summaries of the fit of

each model and refer to each part as needed in the text, instead of making

individual tables for each component.

o Avoid using R output taken directly from R/RStudio. Instead create your own tables

where you select only the relevant pieces of the output to display.

o Generally, the methods and results sections tend to be the longest sections, while the

introduction and discussion tend to be shorter.

o Keep this in mind when deciding how much background to provide in your

introduction. Often just a paragraph or two is plenty, given the word limits in this

project.

o However, make sure you leave yourself enough space for a solid discussion

where you can discuss the impact of the limitations that may exist in your model.