Statistics for Design Researchers

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Contents

ME305: Overview

ME305 is a comprehensive yet friendly introduction to the fundamental concepts of inferential statistics, primarily used in survey research. Course content is delivered via online video lectures, with group classroom time dedicated to completing the lab assignment. All examples and assignments involve writing code in R, interpreting R output and creating visual output with ggplot2. Two-unit credit requires completion of an analysis project using data collected as part of an NSF-funded engineering education research project. Auditors welcome.

Course Learning Objectives

The objectives of ME305 are for students to acquire:


  • The fundamental concepts of inferential statistics, primarily used in survey research
  • A working knowledge of R statistical software for data analysis
  • The skills necessary to create, launch and collect data from an online survey tool (Qualtrics)
  • The ability to create simple graphical representations of statistical data
  • Confidence in describing statistical results to others

Instructors and Syllabus

Qu Jin (qujin@stanford.edu) and Mark Schar (mfschar@stanford.edu) Office Hours by appointment

Syllabus

Location and Time

  • Second Floor – Center for Design Research (Building 560)
  • Wed 2:15 PM - 3:30 PM
  • 03/31/2014 - 06/04/2014
  • Mandatory attendance required for first class. Laptop recommended.

Homework as Pre-Work

The seminar will use an “inverted classroom” approach. All lecture videos and R-scripts will be posted to the class website at least one week prior to class. It is the student’s responsibility to watch the lecture videos and attempt the statistical techniques prior to class session. We estimate that it will take about 1.5 hours of pre-work for each class session.

Class Sessions

Class sessions will focus on a discussion of the specific statistical technique that is the subject of the week. There will be a brief review of the statistical terms and definitions, a quick review of the R-script commands and output and a longer discussion of how this technique is used in research. Published examples of the statistical technique in discussion may be introduced and discussed in class.

Final Project

Students who take ME305 for credit will be required to complete a Final Project. The project will involve the analysis of a data set (either students choice or instructor provided). The project will be graded on a 10-point scale:

  • 5-points for five examples of statistical techniques (i.e., means, correlations, t-tests, regression, mediation),
  • 3-points for three examples of graphical data representation and
  • 2-points for class presentation.

Class Materials

Lecture visuals, sample data sets, R scripts and other links will be made available on the class website. Lectures will be made available via a special site on Coursera. The Coursera materials are for personal study and research only. The professor featured in the videos is Dr. Andrew Conway of Princeton University, who has agreed to the use of these materials, but is not responsible for the overall content of this course.

Coursera

Week 1 - Orientation

Download and install R

Optional: R Studio

Week 2

Week 3

Week 4

Week 5

Week 6

Week 7

Week 8

Week 9

Week 10

Personal tools