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Statistics and Design of Experiments Using R


May 2021


 About this course 


This course aims to make its participants proficient in the fundamentals of statistics, the statistical design of experiments, and in the use of the programming language R for performing statistical computations. Participants will learn how to recognize which statistical methods or designs are appropriate for a given context, compare between alternative statistical approaches, and perform computations using R to draw statistical conclusions.

This course is designed for professionals and students in technical fields who want to learn the fundamentals of statistics, how to design efficient experiments that reach a statistical conclusion, and how to use R in the statistical exploration, visualization, and analysis of data. These participants can identify with profiles 2 and 3 (university and technical) of the 2-3-1-20-5 convocation.
Participants need to be computer literate and have a laptop. Previous knowledge of statistics or programming experience using R is not necessary, but helpful. Participants need to understand and speak English, and have a grade of at least A2 in the free test www.examenglish.com/leveltest/index.php
This course will be taught online through Zoom for Education or MS Teams. It will consist of 10 meetings, 3 hours each (30 hours in total). Classes will be held on weekday evenings for two consecutive weeks, from 5 PM to 8PM.


 Method of instruction 

Classes will be a mix of presentations to convey concepts, working through examples, and group exercises. Each week, students will be randomly assembled into groups of 2 or 3, and must complete an in-class assignment based on the material covered. In addition, participants must take an individual quiz at the start of each class about the materials covered the previous day. All instruction and materials will be in English. The teacher for this course ir Dr. Tim Matis.


Attendance is mandatory, and any student who does not attend at least 90% of the meetings will automatically fail the course. The participant’s grade will be based on in-class group work (60%) and individual quizzes (40%).

 Course Materials 


The software used in this class are free for personal use.


Class Schedule & Syllabus



Associate Professor of Industrial, Manufacturing and Systems Engineering

Dr. Timothy Matis has a Ph.D in Philosophy in Industrial Engineering, and master's and bachelor's degree of Science in Industrial Engineering. He is currently a professor at Texas Tech University and provides periodic research and teaching assistance to the School of Engineering at the Pontífica Universidad Católica de Valparaiso as a visiting professor. 

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