Student Learning Outcomes

The steering committee, working on revising the College GAISE report, would appreciate your valuable feedback on a draft set of student learning outcomes developed for Introductory Statistics courses. These outcomes are designed to clearly articulate the knowledge, skills, and abilities that our students are expected to achieve by the end of a introductory course and will be included in the revised College GAISE

Your input is crucial in helping us meet our goal of providing SLOs that are:

  • Clear
  • Comprehensive without being restrictive
  • Applicable to a variety of different types of courses
  • Useful to students and instructors

DRAFT Introductory Statistics Student Learning Outcomes

After completing an Introductory Statistics Course, a student should be able to:

  1. Identify cases and variables in a data set, including multivariable data sets.  Recognize whether variables are categorical or quantitative.
  2. Assess how the data were collected, and recognize how data collection affects what conclusions can be drawn from the data.  Explain the importance of random sampling and random assignment; know the distinction between the two.
  3. Identify appropriate graphs and summary statistics for variables and relationships between variables, and correctly interpret information from graphs and summary statistics.
  4. Use software or apps to create visualizations, produce summary statistics, and carry out the computational aspects of statistical analysis.
  5. Explain the importance of random variation in statistical inference.  Recognize that statistical inference involves generalizing from a sample to a population.
  6. Identify appropriate methods to use in statistical inference, and interpret results from those methods.   
  7. Understand that conclusions drawn from statistical inference might be wrong, due to sampling variation.  Recognize the problem of publication bias and the key importance of replication.
  8. Demonstrate effective use of predictive models, such as regression lines. 
  9. Evaluate ethical issues in statistical practice.
  10. Effectively communicate results obtained from data.

Please use this form to provide feedback.