# Why a statistics capstone assignment is considered a summative assessment of the complete course?

July 09, 2024
Dr. Alex Thompson
United States
Capstone
Dr. Alex Thompson, Ph.D. in Statistics from UC Berkeley, has 12+ years of experience in statistical software (R, SAS, SPSS) and data analysis techniques (multivariate, time series). Renowned for innovative teaching and personalized support, Dr. Thompson excels in making complex statistical concepts accessible to all students.

The capstone assignment is your opportunity to think concretely about what students ought to be able to do at the conclusion of your course that they couldn't do (or couldn't do as well) at the start. This may be done after setting your course goals, or designing the capstone assignment may provide the opportunity to clarify and refine your course goals and objectives. We recommend first considering what mastery looks like "in the wild"—what does it look like when a CEO does that thing well? What does it sound like when you overhear a professional talking about that subject at the conference bar? From there, you can consider how that mastery can be simulated "in captivity" in the classroom.

In the context of a statistics course, tools such as R, SAS, STATA, and SPSS come into play. Mastery might involve using these tools to analyze complex datasets, create compelling visualizations with Tableau or PowerBI, and apply statistical methods to real-world problems.

A capstone is a summative assessment, and as such, it should provide opportunities to synthesize large amounts of content and/or skills and to engage with course material creatively. For example, using Excel to manage and analyze large data sets or MyMathLab to solve intricate statistical problems reflects this synthesis. In designing a cumulative, synthetic, or synoptic exam or final project, you should think carefully about what kind of mastery you are assessing and about how best to ask your students to demonstrate it. For students seeking assistance with capstone assignments, this reflection is critical in guiding their understanding and execution of their final projects."

## Synthesizing Knowledge and Skills

If you have read our page on taxonomies of learning, you will know that different "assignment verbs" correlate to different levels of sophistication. Asking students to "list" the causes of the French Revolution, for example, is a relatively low-order question. In a statistics course, you might instead ask students to "analyze" a data set using R or to "evaluate" the results of a time series analysis performed with STATA. Higher-order tasks like "apply," "evaluate," and "create" require students to take what they have been taught and use it to perform a new action, such as conducting a hypothesis test with SPSS or developing a business analytics model with PowerBI.

## Common Genres of Capstone Assignments

In addition to the content of the assignment, the form matters as well. Some of the most familiar types of summative assessment are exams and term papers. However, the best capstone assignments are those created after careful consideration of the course's goals and objectives. For instance, if you want to measure students' ability to retain and recall content from the course, an exam is a great tool. However, if you want to measure students' ability to synthesize secondary materials in support of a research question, a term paper might be ideal.

In statistics, this could mean using XLSTAT or MegaSTAT to analyze survey data, or applying econometric models using GRETL. For those looking to integrate more advanced techniques, assignments might include multivariate analysis or panel data analysis using tools like MySTATLab or XLMINER.

If you hope to have students test one or more academic claims against what those claims allow them to do in the world, or to encourage students to become translators and ambassadors of their academic learning, you will want a capstone that connects their learning to the wider world. This might involve using their statistical skills in community engagement projects or public teaching scenarios, such as a poster presentation on the applications of biostatistics or a gallery installation showcasing results from an operations research project using Linear Programming.

Assigning a creative or "non-traditional" assignment can require extra preparation but can be more effective tools for student learning. These assignments might involve using MyMathLab for advanced quantitative methods, conducting probability studies with Connect Math, or utilizing JAMOVI for psychological statistics. Often, they are designed so that students receive feedback from multiple sources—their peers, an audience—in addition to the instructor. For example, a project using Witness to simulate real-world processes or applying econometrics models in a public policy context can provide robust feedback mechanisms.

## Integration of Various Statistical Tools

Throughout the capstone project, integrating various statistical tools and methodologies is crucial. This integration might involve using Tableau for data visualization, SAS for complex data analysis, or SPSS for hypothesis testing. Incorporating business analytics with PowerBI, or conducting biostatistical analysis with Excel, demonstrates the practical application of these tools. Students might also engage with advanced topics like panel data analysis, time series analysis, and multivariate analysis using specialized software like STATA or R.

## Conclusion

In conclusion, a statistics capstone assignment is a comprehensive summative assessment that encapsulates the entire course's learning objectives. It challenges students to synthesize knowledge and skills acquired throughout the course, using various statistical tools and methodologies. From hypothesis testing in SPSS to data visualization with PowerBI and Tableau, the capstone project showcases the students' ability to apply their learning to real-world problems, making it an essential component of the statistics curriculum.