Engineering Statistics - A Conceptual Approach (Spring 2022 TA)

Teaching Assistant

My primary responsibilities were grading homework assignments (8), lab assignments (3), and projects (3). In addition, I proctored two synchronous exams and promptly answered and clarified any questions students had. I provided solutions and detailed feedback on student work and created notes on coding examples for lab projects. To ensure effective communication and support, I maintained a high level of organization and made sure the students’ grades were accurate. I made myself readily available to students via prompt email responses, virtual office hours, and assistance both during and outside of working hours. Additionally, I closely monitored students’ progress throughout the semester and scheduled Zoom meetings with students to address any questions or concerns that arose during the course.

Textbooks

• Required Textbook:
  • Douglas C. Montgomery and George C. Runger, “Applied Statistics and Probability for Engineers”

Course Description

This course covers topics in statistics relevant to engineering, while also addressing the conceptual understanding of these topics and their relevance to real data. This course is part of the Statistical and Inferential Reasoning Section, and therefore must also discuss how to evaluate common claims that address confidence intervals, hypothesis testing, and statistical constructs, such as charts, graphs, numerical summaries, tables, etc. This course also helps students improve their information literacy by identifying and utilizing relevant resources and communicating the synthesis of these resources. Course topics include probability, discrete and continuous probability distributions, discrete and continuous random variables, expected values, variance, random sampling, descriptive measures for data, hypothesis testing and confidence intervals for one- and two-sample problems, linear regression, correlation, and statistical control charts.

Student Learning Outcomes

The primary goals of this course are:

• Use statistical methodology and tools in the engineering problem-solving process.
• Compute and interpret descriptive statistics using numerical and graphical techniques (using software, where appropriate).
• Understand the basic concepts of randomness, probability, random variables, probability distributions, and cumulative distribution functions.
• Compute point estimates of parameters, understand sampling distributions of various statistics, and understand the Central Limit Theorem.
• Construct confidence intervals and hypothesis tests for one and two parameters and gain a conceptual understanding of these methods as encountered in daily life.
• Compute the correlation coefficient, simple linear regression lines for bivariate data and understand issues surrounding correlation such as confounding and causation.
• Construct statistical control charts, using software.

Software

R.