Course Resources

This page contains various resources to support your learning in ISE 315 Engineering Statistics. The resources are organized into categories for easy navigation.

1. Textbooks & References

Required Textbook

• D.C. Montgomery and C. Runger, Applied Statistics and Probability for Engineers, 6th Edition, Wiley, 2013
  • Publisher’s Website

Reference Books

• R. Walpole and R.H. Myers, Probability and Statistics for Engineers and Scientists, 9th Edition, Pearson, 2011
• J.L. Devore, Probability and Statistics for Engineering and the Sciences, 9th Edition, Cengage, 2016
• G.G. Roussas, An Introduction to Probability and Statistical Inference, 2nd Edition, Academic Press, 2015

Online Resources

• NIST/SEMATECH e-Handbook of Statistical Methods - Comprehensive reference for statistical methods
• OpenIntro Statistics - Free statistics textbook
• Stat Trek - Statistics tutorials and resources

2. Lecture Materials

Slides

• Lecture slides will be posted on Blackboard before each class
• Sample Lecture: Review of Estimation

Recordings

• Available on Blackboard (requires login)

3. Statistical Tables

Essential statistical tables for the course:

• Standard Normal (Z) Table
• t-Distribution Table
• Chi-Square Distribution Table
• F-Distribution Tables

4. Software Tools

Recommended Software

Python

• Python - General-purpose programming language
• NumPy - Numerical computing
• SciPy - Scientific computing (includes statistical functions)
• Pandas - Data manipulation and analysis
• Statsmodels - Statistical modeling
• Matplotlib / Seaborn - Data visualization

R

• R - Statistical computing environment
• RStudio - IDE for R

Other Tools

• Minitab - Statistical software (commonly used in industry)
• JMP - Statistical analysis software
• Excel - Data Analysis ToolPak

Online Calculators

• StatKey - Interactive statistics tools
• GeoGebra Statistics - Probability calculator
• Social Science Statistics - Various statistical calculators

5. Tutorials & Examples

Video Resources

• Khan Academy - Statistics - Free video tutorials
• MIT OpenCourseWare - Statistics - MIT course materials
• StatQuest with Josh Starmer - Engaging statistics explanations

Python Tutorials

• SciPy Statistics Tutorial
• Statsmodels Documentation

6. Topic-Specific Resources

Estimation & Confidence Intervals (Chapters 7-8)

• Confidence Interval Tutorial
• Central Limit Theorem Visualization

Hypothesis Testing (Chapters 9-10)

• Hypothesis Testing Overview
• Type I and Type II Errors

Regression Analysis (Chapters 11-12)

• Simple Linear Regression Tutorial
• Multiple Regression Guide

ANOVA (Chapter 13)

• ANOVA Tutorial
• One-Way ANOVA Calculator

Design of Experiments (Chapter 14)

• Factorial Design Introduction
• DOE Tutorial - NIST

7. Practice Problems

• End-of-chapter problems from the textbook
• Additional practice problems on Blackboard
• Practice Problems - Penn State

8. Formula Sheets

A comprehensive formula sheet will be provided for exams. Key formulas to know:

• Point estimators (sample mean, sample variance)
• Confidence interval formulas
• Test statistics (z, t, chi-square, F)
• Regression coefficients
• ANOVA F-statistic

9. FAQs

• What prerequisites do I need for this course?
• Which calculator can I use for exams?
• How do I access Blackboard?