Engineering Statistics Modules

Developer: Dr. Steven Jiang at NC A&T
Course: Engineering statistics course that is primarily taken by sophomores and juniors
Knowledge Prerequisites: None
Data Tool(s): Github Classroom and Google Colab - is scaffolded such that students who have no programming experience are able to leverage statistical analysis libraries
Module Focus:
- Introducing students to these data science tools and data science topics, such as descriptive statistics, inferential statistics, and
  visualizations, so that the students can leverage their knowledge to solve engineering statistics related problems. In both modules, students analyze real-world data such energy use in buildings (Basic Statistics module) and stormwater runoff (Hypothesis Testing module).
Keywords (Disciplinary-Specific): engineering statistics, energy use in buildings, stormwater runoff
Keywords (Data Science): descriptive statistics, histograms, scatter plots, boxplots, confidence intervals, hypothesis testing

Basic Statistics Module	Hypothesis Testing Module
Targeted Data Science Topics and Competencies Data Use (Statistical Analysis): Demonstrate an ability to use statistical methods and/or software pertaining to an analysis goal Demonstrate an ability to identify appropriate subset of data for an analysis goal Data Visualization (Data Communication): Demonstrate an ability to create a graphical or tabular representation of data Data Visualization (Data Interpretation): Demonstrate an ability to interpret graphical and tabular representations	Targeted Data Science Topics and Competencies Data Preprocessing (Data cleaning) Demonstrate an ability to detect and deal with outliers in data Data Visualization (Data Communication) Demonstrate an ability to create a graphical or tabular representation of data Data Visualization (Data Interpretation) Demonstrate an ability to communicate concepts and findings using graphical or tabular representations of data Data Use (Statistical Analysis) Demonstrate an ability to formulate a hypothesis, prediction, or goal to be targeted using data analysis Demonstrate an ability to identify appropriate statistical methods and/or software for an analysis goal Demonstrate an ability to identify appropriate subset of data for an analysis goal Demonstrate an ability to use statistical methods and/or software pertaining to an analysis goal Demonstrate an ability to compare results of analysis with other findings Data Use (Data communication) Demonstrate an ability to explain results to an appropriate audience
Module Materials Introductory Materials Instruction Video: Introduction to Google Colab and Module Task Brief Introduction to Data Science: Introduction to data science, why data science and data challenges In-class Demo: Download and open in Google Colab Task Materials Data Set: Real world building data from Vanderbilt University Task Instructions Task: Download and open in Google Colab Task Rubric	Module Materials Introductory Materials Introduction to Hypothesis Testing Module Video Demo: Download and open in Google Colab Task Materials Data sets: Storm Data Set 1, Storm Data Set 2 Task Instructions Task: Download and open in Google Colab Rubric
Download Basic Statistics Module Materials	Download Hypothesis Testing Module Materials

Basic Statistics Module

Hypothesis Testing Module

Targeted Data Science Topics and Competencies

Data Use (Statistical Analysis):
- Demonstrate an ability to use statistical methods and/or software pertaining to an analysis goal
- Demonstrate an ability to identify appropriate subset of data for an analysis goal
Data Visualization (Data Communication):
- Demonstrate an ability to create a graphical or tabular representation of data
Data Visualization (Data Interpretation):
- Demonstrate an ability to interpret graphical and tabular representations

Targeted Data Science Topics and Competencies

Data Preprocessing (Data cleaning)
- Demonstrate an ability to detect and deal with outliers in data
Data Visualization (Data Communication)
- Demonstrate an ability to create a graphical or tabular representation of data
Data Visualization (Data Interpretation)
- Demonstrate an ability to communicate concepts and findings using graphical or tabular representations of data
Data Use (Statistical Analysis)
- Demonstrate an ability to formulate a hypothesis, prediction, or goal to be targeted using data analysis
- Demonstrate an ability to identify appropriate statistical methods and/or software for an analysis goal
- Demonstrate an ability to identify appropriate subset of data for an analysis goal
- Demonstrate an ability to use statistical methods and/or software pertaining to an analysis goal
- Demonstrate an ability to compare results of analysis with other findings
Data Use (Data communication)
- Demonstrate an ability to explain results to an appropriate audience

Module Materials

Introductory Materials
- Instruction Video: Introduction to Google Colab and Module Task
- Brief Introduction to Data Science: Introduction to data science, why data science and data challenges
- In-class Demo: Download and open in Google Colab
Task Materials
- Data Set: Real world building data from Vanderbilt University
- Task Instructions
- Task: Download and open in Google Colab
- Task Rubric

Module Materials

Introductory Materials
- Introduction to Hypothesis Testing Module Video
- Demo: Download and open in Google Colab
Task Materials
- Data sets: Storm Data Set 1, Storm Data Set 2
- Task Instructions
- Task: Download and open in Google Colab
- Rubric

Download Basic Statistics Module Materials

Download Hypothesis Testing Module Materials

Module Intro Video: Steven Jiang

Instruction to use Github classroom and Google Colab for module 1

Introduction to Module 2

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