Integration Of Statistics Throughout The Undergraduate Curriculum: Use Of The Senior Chemical Engineering Unit Operations Laboratory As An End Of Program Statistics Assessment Course
Author(s) -
Darin Ridgway,
Valerie Young,
M.E. Prudich
Publication year - 2020
Publication title -
papers on engineering education repository (american society for engineering education)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.18260/1-2--11491
Subject(s) - curriculum , capstone , computer science , session (web analytics) , descriptive statistics , statistics , statistical analysis , unit (ring theory) , mathematics education , engineering education , course (navigation) , engineering , engineering management , mathematics , psychology , pedagogy , algorithm , world wide web , aerospace engineering
Graduates of chemical engineering programs should have the ability to use basic statistical techniques to analyze and interpret process and experimental data. Chemical engineers should also have the ability to identify the statistical appropriate tool to accomplish a specific data analysis task. This paper describes the undergraduate course of instruction in statistics in the chemical engineering program at Ohio University. This course of instruction begins with a basic introduction to linear regression which takes place in a freshman-level chemical engineering computing course, includes a junior-level course devoted to statistical analysis and experimental design, and ends with the application of statistical data analysis tools in the senior-level unit operations laboratory course sequence. Spreading the exposure to statistical analysis across the curriculum permits longitudinal reinforcement of important concepts and skills. Special emphasis is placed on the use of the senior-level unit operations laboratory experience as a capstone statistics usage and assessment tool. This course provides the students with an opportunity to break out of the "chapter box" which is often characteristic of stand-alone statistical methods courses. The courses also emphasize the point that experimental planning and design includes not only the selection of the experimental parameters to be studied, but also the planning of the data analysis and statistical treatments to be utilized in the interpretation of the experimental data that is acquired. The proper assessment of statistics-related performance in the senior-level laboratory courses provides end-of-program assessment data on student statistical skills and abilities.
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