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Sample Rubric for the Final Project When Using Introduction to Business Analytics, 2024 Release

Published Date
Author Vern Richardson

I provide students with a rubric for their final project that sets the expectations of what needs to be done across 8-10 categories, using the SOAR model as the foundation. This allows them a frame for their work and allows them to ask me for specific suggestions on what could/should be done.  (Project ideas and specifications are in Chapter 12 in Introduction to Business Analytics). 

I think by providing the students with a rubric like this, they can see the depth and breadth of the project. They can also use it to ask me direct questions about what they need to do to complete the project. 

I generally have the students grade their project, to state how they think they have performed.  As an instructor, I will grade it from there, but this causes students to think they have performed. 

Rubric for the Final Project – You grade it! 

Criteria for Grade 

Subcriteria 

Above Expectations 

Meets Expectations 

Below Expectations 

Specify the Question (10 points possible) 

____/ 10 

Scope of Question 

Specific questions asked with appropriate scope that will be addressed by the data analysis.  

Question specificity lacking or scope of question too big or too small, to be answered by data. 

Question specificity lacking and scope of question too big or too small, to be answered by data analysis. 

Specify the Question (10 points possible) 

____/ 10 

Hypothesis Development 

Hypotheses developed and stated about the results you expect to find. 

Hypotheses are stated, but not developed. 

Hypotheses not contemplated or stated. 

Obtain the Data 

(10 points possible) 

____/ 10 

Data Selection 

Data Source Reliable, Analyzing this data will directly address the question asked 

Data source reliability may be questionable and may or may not completely address the question asked. 

Data source is not reliable and will not adequately address the question asked. 

Obtain the Data 

(10 points possible) 

____/ 10 

Data Cleaning 

Data cleaned and coherent strategy for cleaning missing data stated and executed. Data Prepared for Analysis. 

Data cleaned, but no coherent strategy for cleaning data is used. Data preparation not complete. 

Data lacks cleaning. No coherent strategy for cleaning data is used. Data preparation not complete. 

Criteria for Grade 

Subcriteria 

Above Expectations 

Meets Expectations 

Below Expectations 

Analyze the Data 

(10 points possible) 

____/ 10 

Analysis performed, including variety of analytics types and techniques. 

Three or more types of analytics performed. 

Four or more analytics techniques used. Appropriate conclusions drawn. 

Two or more types of analytics performed. 

Three or more analytics techniques used. Appropriate conclusions drawn. 

One type of analytics performed (descriptive, diagnostic, predictive or prescriptive). Two or more analytics techniques used. Appropriate conclusions drawn. 

Analyze the Data / Report the Results 

(10 points possible) 

____/ 10 

Visualizations 

Unique, clever visualizations, used and insightful conclusions drawn. 

Visualizations that match analysis performed. Basic conclusions drawn. 

Simple visualizations done without any useful insight. 

Report the Results 

(10 points possible) 

____/ 10 

Report and Presentations 

Report / Executive Summary / Presentation looks professional and appealing.  Appropriate color used.  

Report / Executive Summary / Presentation complete. 

Report / Executive Summary / Presentation not complete. 

Overall Project  

(30 points possible) 

____/ 30 

Bloom’s Taxonomy – Level of Critical Thinking Achieved 

Evaluate and/or Create Critical Thinking Level Achieved 

Apply and Analyze Critical Thinking Level Achieved 

Remember and Understand Critical Thinking Level Achieved 

About the Author

Vernon J. Richardson is a Distinguished Professor of Accounting and the G. William Glezen Chair in the Sam M. Walton College of Business at the University of Arkansas and a visiting professor at Baruch College. He received his BS. Master’s of Accountancy, and MBA from Brigham Young University and a PhD in accounting from the University of Illinois at Urbana-Champaign. He has taught students at the University of Arkansas, University of Illinois, Brigham Young University, and University of Kansas and internationally at Chinese University of Hong Kong Shenzhen, Aarhus University, the China Europe International Business School (Shanghai), Xi'an Jiaotong Liverpool University, and the University of Technology Sydney. Dr. Richardson is a member of the American Accounting Association. He has served as president of the American Accounting Association Information Systems section. He previously served as an editor of The Accounting Review and is currently an editor at Accounting Horizons. He has published articles in The Accounting Review, Journal of Information Systems, Journal of Accounting and Economics, Contemporary Accounting Research, MIS Quarterly, International Journal of Accounting Information Systems, Journal of Management Information Systems, Journal of Operations Management, and Journal of Marketing. Dr. Richardson is also a co-author of McGraw-Hill’s Introduction to Data Analytics for Accounting, Data Analytics for Accounting, and Introduction to Business Analytics textbooks.

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