Statistics homework help

1
ADA-I Research Project guidelines v. 10/22/20
Goal:
To demonstrate proper understanding of key course concepts by applying them to a public dataset of
your choice.
What to submit: NOTE: For Friday class the dates shown are one day later
Document Format Score
impact
Under which assignment to
submit
Due date
(all at
6:00pm)
Link Exact link to a public dataset
you will use
URL 3% Chat Room 11/5
1a
1b
Proposal (this is also the first
sections of your project writeup)
Dataset file (s)
PDF
CSV
17% Course Project Supporting
Material
Course Project Supporting
Material
11/14
2
3
Project write-up – original
document
Project write-up – PDF version
document
MS Word
PDF
50% Course Project Supporting
Material
Course Project
12/3
4a
4b
Data Analysis in Excel
And / or
Data Analysis in a Python
Jupyter Notebook and its PDF
version
.xlsx
And / or
.ipynb
.PDF
15% Course Project Supporting
Material
Course Project Supporting
Material
5 Presentation slides MS
PowerPoint
15% Course Project Supporting
Material
12/6
Late submission for any component may result in 1% grade reduction for the whole project per 0.01-24
hours being late. Submissions after the presentation slides due time will not be accepted (respected
component receives zero points).
Process:
• This is teamwork but each student must submit a copy of all documents. Each team of 3 students
selected will work together to complete the project
• Team composition will be provided via the respective assignment. One team member will be assigned
as the team lead with responsibilities to ensure that teamwork is taking place in a timely manner and
versions of documents to submit are synchronized amongst members
• A link to the public dataset to be used by each team needs to be submitted by the team lead, or a
delegate by its due time by adding the link to the chatroom under NYU Classes. The same dataset
2
cannot be used by more than one team. If the link has already been entered in the chat room a
different dataset must be selected: add your link soon to reserve a dataset
• Each student submits the same copy of all materials listed below that the team worked on (only one
of these student submissions will be selected randomly and used for grading the whole team)
• The top right section of each page of the writeup must include the name of the student(s) who
worked on that page. The amount and quality of work completed by each student will be used to
increase or reduce individual grading
• Google groups is suggested to be used for collaboration.
Other important details:
Main topic (Research statement):
Present a research question, describe the data you use, your expectations regarding insights you will
derive, assumptions made and potential results from your study which could falsify your theory.
Components
1. Proposal
A 6 (+/- 2) total pages PDF document outlining your
• research question (statement) – This may be modified later for the final writeup
• dataset you will use and description
• draft answers to sections III.1 and III.2 sections (below) of your project write-up
2. Final project write-up
• details on next page
3. Presentation slides
• Minimum of 5, maximum of 10 slides, summarizing your write-up
General
• All document filenames need to start with “Team# Your Last name First name ADA-I Project aaa”,
where “aaa” is the name of the document (e.g. proposal, paper, analysis, presentation, data…)
• All documents that you submit must include a cover page or a cover section with the title “Course
Project: bbbb”, where “bbbb” is the name of your project, your team number and the names of your
teammates with your name underlined, the name of the document itself and the date completed, the
course name, course number, semester, the professor’s name in this order
• On each page you need to include a footer with your team number, project name and page/slide
number
• You need to use either Excel and / or Python notebooks for your analysis and insights gathering.
Include visualizations to support your findings
• Your dataset needs to have a minimum of five (5) features with a population of at least 1000 items
• Your final project write-up must be a minimum of 4,000 words or 8 pages long (maximum 15),
excluding visualizations, dataset, code/spreadsheets and other attachments or reference material
• Format: single spaced, font Calibri 12 point
3
• Your paper document should include proper citations, as applicable. Use the library guidelines on how
to cite: http://guides.nyu.edu/citations .
Research paper (write-up) composition and related notes
• Your project should demonstrate use of all below Data Analytics concepts.
• You should describe the steps you take, the visuals, your conclusions and other detail that would
help the reader understand the work completed.
Section / focus area Notes and What is important
I. Research statement 1-2 paragraphs to describe clearly what your paper examines and
why it is important
II. Dataset description 1 paragraph description of the data, including links to the
dataset(s)
III. Applied Data Analytics Include detailed descriptions of your work in each subsection.
Include a minimum of 2 paragraphs for each section to describe
your findings. You will need to:
• Demonstrate applicability and use of key course concepts
• Start with a summary of what analysis you did in this section III
and of the steps taken in each subsection
• Conduct data transformation, where applicable, and include a
description on what was done and why
1. Data visualization and
exploration
Initial data exploration and related visualizations
2. Descriptive Statistical
Measures
Applying related concepts to better understand data and potential
relationships
3. Random Sampling and
Probability Distributions
Demonstrate application of related concepts
4. Sampling and
Estimation
Obtain various samples and apply related principles
5. Statistical Inference Using samples, conduct tests related to your hypothesis and
interpret the results obtained
6. Regression Analysis Conduct regression analysis, apply a systematic approach to build
your regression model and test your prediction results
IV. Conclusions Summarize your analysis, insights obtained, existing or potential
results that may falsify your conclusions and suggested next steps
Up to 5% of your project grade is based on overall clarity in thought process, grammar, syntax,
completeness, proper format regarding citations and document/section labels.
Please use the above entries under Section / focus area as section headers in your writeup.

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