For any course in a student's degree program, the assessment should be part of an integrated assessment and learning package, with the components of the package combining to meet the learning objectives in a steady development of skills and operational knowledge that take account of the students' various prior and future learnings. This paper considers such a package for an introductory course in probability and distributional modelling, including its objectives with reference to the nature of statistical thinking in probabilistic and distributional modelling, and general assessment principles. A new component of assessment to strengthen the problem-solving environment and to better address some of the objectives is described, together with student and tutor feedback and student data.
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The CAUSE Research Group is supported in part by a member initiative grant from the American Statistical Association’s Section on Statistics and Data Science Education