About
This series of modules is designed to help reinforce your existing knowledge of statistics and teach you some of the ways chemists commonly calculate and communicate uncertainty. This module is new (2018) and your comments on it are appreciated.
The modules pair with online question practice and online quizzes (via Alchemy). You will probably find some of the module content is already familiar. Rather than read through all the module content, you are encouraged to start with the practice questions as a
way to find out if you have any misconceptions or gaps in knowledge. Feedback for incorrect answers will direct you to the appropriate part of the modules.
Module 1: Fundamentals of Statistics
Much of this content is review of material from CHEM211 and/or STAT200. For this module, there is no requirement to have taken either of these courses.
Learning Objectives
By the end of this module you will be able to:
- A) List and classify common sources of variability in chemical measurements
- B) Describe the characteristics of a normal (Gaussian) distribution
- C) Describe or interpret the following terms: relative error, mean, sample standard deviation, standard deviation of the mean, confidence level, confidence interval
- D) Explain or predict how standard deviation of the mean and confidence intervals depend on the number of replicate measurements and on the confidence level
- E) Given numerical data for replicate measurements, calculate the mean, sample standard deviation, standard deviation of the mean, and/or confidence intervals
- F) Describe the conditions under which you can or cannot reject an outlier data point and apply an outlier test where appropriate
- G) Apply error propagation to calculate the standard deviation or confidence interval for the products of addition, subtraction, multiplication, or division
- H) Report a result and its uncertainty using appropriate calculations and notation
Module Contents
- 1.1 Preface
- 1.2 Types of Uncertainty
- 1.3 Normal (Gaussian) Distributions
- 1.4 Terminology
- 1.5 Propagation of Uncertainty