Research Project Proposal

User Generated


Business Finance

DSCI 5330

University of North Texas


Please go over the Research Project Proposal guideline powerpoint and work with your group to come up with an appropriate project for your team. Create a project proposal (a word or a pdf) and submit it by the end of next week.

The project proposal should contain the following things:

1) Project title

2) A short description of the your research question. What do you wish to research and how do you wish to answer your research question. It doesn't need to be long, a short paragraph is fine.

3) Work will work on what aspect of the project. This can be tentative and can change somewhat later.

Take the topic regarding sports like cricket. Also, please follow the provided document which is in PPT form.
Kindly, follow each the every step from the PPT.

Unformatted Attachment Preview

Spring 2024 DSCI 5330 Research Guide Structure and Foundations What is this project? +What research is not: Finding a data set and then building something around it is not a research project. Don’t just find a data set, do analysis and summarize findings—that is not the point and not enough. Topic! Research, Implications, meaning, narrative. +This project is meant to allow you to drill deeper into the course topics on your own and to gain greater depth of knowledge than can be discovered in one chapter or one week of class. Therefore, your term paper topic will be a subset of the broader knowledge area +Its for your benefit to gain insights. The Research Question + Research of any kind is done in order to answer a question that you have + Questions for research are normally posed as “how” or “what” questions + The research is “exploratory” and the object is to inform the audience and hopefully learn a few things and wow em on a job interview Examples How is analytics used in online advertising? How have process industries adopted AI/ML? What benefits have retailers realized from business analytics? How has prescriptive analytics been used in Healthcare? How has analytics changed the Finance function in organizations? What applications of ML/AI are used in retail supply chain? How has sentiment analysis/social media analytics changed political campaigns? What are emerging applications of analytics in the aerospace industry? Wikipedia and Google… Wikipedia Wikipedia is not peer-reviewed or checked for accuracy and therefore is NOT a credible or allowable reference source. However, you can wikipedia as a “portal” on a topic to find the references at the bottom of the entry and go directly to those sources for your information. Google—it’s a basic start. Google Scholar is much better The Library + Contrary to popular belief you cannot find everything online in google for free. + We have an excellent library at UNT. + The best information is available in the myriad data bases available to you as a UNT student at the library. If you were a private individual and wanted access to just one of these data bases it would be over $100k per year. There is gold at the library and the data bases (ABI inform is awesome for example). Mine the gold please! Writing your paper Four steps Outline Write and Cite Edit and Review Finalize Start with an introduction to provide a paragraph about the purpose of the paper and why it is important to BI/A. Detailed Suggestions b. Include any information on the state of this topic and any evolution of progress within the last 5 – 10 years. This might include industry reports or white papers, publications in industry related journals, or consultant reports like those from Gartner, TDWI, etc. You should not use blogs or website verbiage. c. Include the major issues surrounding the use/implementation/management of the topic. This may include published examples of detriments when poorly used or ignored and examples of benefits when properly implemented. And more…. + Include major obstacles or impediments to the use/implementation/ management of the topic. + + e. Include, if appropriate, any software that might facilitate the use/implementation/management of the topic. (This won’t apply to all topics.) In this section, you also need to include a list of the top vendors for the software. + + f. Include anything else that you find useful in learning about this topic. + + g. Provide a summary and conclusions section that summarizes your paper in a paragraph or two and provides your thoughts for the future of this topic in another paragraph or two. More suggestions… + The paper should be 8 – 10 pages (exclusive of cover page, reference list, and any figures or tables you might choose to use). + + b. It must be double spaced with 1 inch margins all around. + + c. Use Times New Roman 12 point font. More strong suggestions. + Cite your sources using a standard referencing guide – I would expect at least 10 references + Use in-text citation style or footnotes + No end notes + Remember to cite sources on tables and figures + Refer to a standard reference guide for examples Key Details--how you do anything is how you do everything Grammar and spelling Recommend downloading Grammerly for free Referencing Labeling Flow of ideas Format consistency
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Explanation & Answer



Project Proposal: Making Cricket Performance Analysis Better with Machine Learning is
going on.

Student’s Name
Institutional Affiliation
Course Name and Number
Supervisor’s Name
Due Date


Project Title:
"Revolutionizing Cricket Analysis: "Machine Learning leveraging to improve performance
insights is a key aspect of our business strategy.”
Can one sport occupy a greater stage in the world like cricket does? Indeed, the reason
why cricket at the moment is attracting more and more interest in the minds of the global
population is the fact that it is not only rich in history as well as being the favorite sport of many
people all over the globe but also because of the highly advanced data collection and analytics
technology. Our project is intended to find the possible integration of the methods of machine
learning aimed at enhancing the performance analysis of cricket through the use of match logs.
Whether in terms of batter or bowler, fielder, or overall tactical approach, teams and players can
struggle to push the envelope of superior performance by channeling data-driven intelligence.
Thanks to the algorithms designed to inform the models and predict outcomes, this technique
allows the best insight due to analyzing every crucial factor during the matches, including
players' performance, opposition strategies, and match dynamics, helping the teams make
reasonable on and off-field decisions. Also, there is the possibility of using machine learning in
cricket, such as programs for players' training that are individualized and fit for the strengths and
weaknesses of the specific person, which is helpful in terms of the team's success. In sum, this
pursuit represents the big moment and is a milestone on the path of the development of cricket as
a sport, giving place to more thrills and competition on the field for coaches, players, and fans.
Research Questions
1. What is the role of machine learning algorithms in accurate and efficient analysis of the
statistics of the crocket players during matches?


2. How can machine learning models for cricket performance analysis integrate and use
various match condition data in their methods?
3. Which different machine learning techniques are able to detect patterns and trends in
cricket match data, and how do these methods compare among themselves?
4. Given that cricket involves complex multi-dimensional dynamics, what are the main
themes and elements that play the most crucial roles in the predictive capacity of machine
learning models for cricket analytics?
Project Scope
The project will focus on the following aspects:
1. Data Collection and Preprocessing: data collection would include information
gathering of such details as, for example, team compositions, including a list of the
players on the field, substitutions of the players, and their performance metrics during the
matches. In addition to basic task implementation, missing data, weird asymmetry
detection, and normalization of numerical variables may be other routine tasks of
preprocessing used to ensure data readiness for analysis and modeling (Anshuman,
2021). Above this, the integration of historical data along with sensor analytics like
sentiment analysis on match commentary or social media chats can give greater casual
insights into cricket matches.
2. Feature Engineering: In this context, feature engineering in sports analytics involves the
procedure of identifying the independent variables and characteristics that have the
potential to contribute significantly to the p...

I was struggling with this subject, and this helped me a ton!


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