Data Analytics Final Project Rubric Project Goal:  Students will utilize data an

Data Analytics Final Project Rubric
Project Goal:  Students will utilize data analysis skills to investigate a chosen topic, draw conclusions, and suggest future research directions.
Submit a Written Paper that includes the following sections:
Define the Topic and Questions you’re trying to answer
Mention your initial assumptions and why this is interesting
Define your “Target Outputs” – what will answer these questions
Describe the data you used for Analysis
Where did you get the data?
What did you need to do with the data or what data did you ignore?
What did you learn?  
What are the results of your research?
Include your thoughts on What’s Next
What could/should be done next to make the analysis better 
What might be the next set of questions that should be answered
In addition to the paper described above, share the datasets used for Analysis
Where did you get the data?
A Data dictionary for the data you used
What cleaning/transformation/new columns did you need?
In short, submit a written paper that includes all the sections above as well as your  analysis (chart(s),  graph(s), table(s)) and the answers you found.
The language and details should allow any non-expert to easily gain an understanding of the topic.
Cite all sources used.
You can submit the datasets and data dictionary separately.
Needs Improvement 
Topic Selection & Research Questions (10%)
– Clearly defined and relevant to data analytics. – Research questions are well-formed, specific, and answerable with data.
– Topic is somewhat relevant. – Research questions are somewhat formed but might lack focus.
– Topic is not well-defined or relevant. – Research questions are unclear or not answerable with data.
– Topic or research questions are missing.
Data Source Selection (20%)
– Uses multiple, credible data sources (e.g., government databases, reputable research institutions). – Sources are properly cited with justification for their selection.
– Uses one or two credible data sources. – Citation is present, but justification might be weak.
– Uses questionable data sources (e.g., personal blogs, social media). – Citation is missing or incomplete.
– Data sources are not included or not relevant.
Data Analysis & Visualization, including a Data Dictionary (30%)
– Data is cleaned and prepared appropriately. – Clear and insightful charts and graphs are created to support findings. – Charts and graphs are well-labeled and easy to interpret.
– Some data cleaning is done. – Charts and graphs are mostly relevant but may lack clarity or need improvement. – Some labeling issues might exist.
– Minimal or no data cleaning is evident. – Charts and graphs are poorly chosen or ineffective. – Significant labeling issues hinder interpretation.
– Data is not analyzed or visualizations are missing.
Answering Research Questions & Conclusions (20%)
– Paper clearly addresses all research questions in a well-organized manner. – Findings are supported by data analysis and presented with clear evidence. – Well-reasoned conclusions are drawn based on the analysis.
– Paper addresses most research questions, but some organization or clarity issues may exist. – Findings are mostly supported by data, but some gaps in evidence might be present. – Conclusions are presented, but reasoning might be weak.
– Paper only partially addresses research questions or lacks organization. – Findings are not fully supported by data, or evidence is weak. – Conclusions are missing or poorly supported.
– Research questions are not addressed, or Paper lacks conclusions.
Next Steps & Further Research (10%)
– Identifies clear and relevant next steps for furthering research or answering additional questions. – Discusses potential limitations of the current analysis and suggests improvements for future studies.
– Briefly mentions potential for further research but lacks specificity. – Limited discussion on limitations of the analysis.
– No discussion of future research or limitations.
– Missing next steps section.
Professional Presentation (10%)
– Paper is clear, concise, and well-written with proper grammar and mechanics. – Uses appropriate formatting and referencing style (e.g., APA). – Charts and graphs are visually appealing and enhance the presentation.
– Paper is mostly clear and well-written, but may contain some grammatical errors. – Formatting or referencing might be inconsistent. – Some issues with chart and graph presentation (e.g., clarity, aesthetics).
– Paper may contain significant grammatical errors or organizational issues. – Formatting or referencing is inconsistent or missing. – Charts and graphs are poorly presented or ineffective.
– Paper is poorly written, formatted, or lacking visuals.
I will also share a Google doc I got with the sources I have found, what I have done so far, and an outline of how I maybe want the paper to look.  Also, I have to do this “Data Analysis & Visualization, including a Data Dictionary” and don’t know what I am doing with that so if you have data that could be added to that send it my way. Other than all that please let me know of any problems or anything else you will need of me.