Statistical Methods in Research

Authors

• Horahenage Dixon Vimalajeewa, University of Nebraska-LincolnFollow

Date of this Version

Summer 6-5-2026

Document Type

Portfolio

Citation

Peer Review Course Portfolio STAT 801A-700: Statistical Methods in Research

University of Nebraska-Lincoln, 2026

Comments

Copyright 2026, Horahenage Dixon Vimalajeewa. Used by permission

Abstract

This course portfolio documents the design, delivery, assessment, student-learning evidence, and reflective evaluation of STAT 801A-700: Statistical Methods in Research, an online asynchronous service course designed to introduce students from diverse disciplinary backgrounds to foundational statistical reasoning and applied data analysis. The course is a non-calculus-based introduction to statistical methods used to answer research questions, with emphasis on collecting, organizing, describing, analyzing, and drawing conclusions from data. The course also emphasizes applications relevant to biology, agriculture, and other research-oriented fields. This is an online distance course aimed to develop students’ understanding of basic probability and statistical concepts, recognize the importance of statistics in research, categorize fundamental data-analytic problems, and assess the steps involved in data collection, organization, processing, and analysis.

Because the course served students from different departments and was delivered asynchronously, the instructional design prioritized flexibility, guided structure, repeated practice, and timely support. The main course activities included prerecorded lectures, guided note-making prompts, weekly quizzes, weekly laboratory assignments, Canvas discussions, office hours, optional interactive Zoom sessions, and instructor/TA support. Lecture materials were intentionally prepared so that students could watch videos, read prompts, listen to explanations, solve examples by hand and with software, and create their own reference notes for future statistical use.

Mid-term survey results indicated strong student satisfaction, with an overall mean of 4.55 out of 5 and 87.8% of ratings at 4 or above. Students especially valued the labs, practical software work, examples, assignments, quizzes, recorded lectures, and timely feedback. The final course evaluation provided additional evidence of positive student experience, with a high response rate of 31 out of 39 students, or 79.49%. Students rated feeling welcome and respected at 4.61, knowing where to go for help at 4.60, instructor communication at 4.47, and useful feedback at 4.35. The most frequently identified beneficial course element was Course Learning Materials and Tools, selected by 51.61% of respondents.

The main area for improvement across both mid-term and final evaluations was interaction. Students valued the flexibility of the asynchronous course but reported fewer opportunities to learn with and from other students. This portfolio therefore reflects on how to preserve the strengths of the course while adding more meaningful, flexible, and low-stakes interaction opportunities in future offerings.