This class format is in-person, with up to 25% online instruction.
D2L is used only for weekly exams and the final exam. All weekly topic lists, lecture notes, online practice exercises, and interactive statistics learning apps are available exclusively on the course website, not on D2L.
The course materials are structured in a modular format, with each module focusing on a specific topic or theme. Each module includes a dedicated web page containing a topic list, links to lecture notes (which feature embedded short videos), online practice exercises, and ISLA apps for self-assessment to gauge your understanding. At the end of each week, you will take a weekly exam through D2L covering all topics from the module of the week.
We will cover one module each week, which are structured in the right navigation panel on the course webpage (https://pengdsci.github.io/MAT121SP26/). After each class, you are encouraged to follow the suggested workflow:
Study the module notes. For each module, you are expected to:
After completing each module, go to D2L to take the corresponding weekly quiz, which covers that module’s topics.
To find the weekly exam on D2L,
To enhance your learning experience and achieve your goals, I offer the following advice:
Start early on weekly materials—never wait until the last minute. Procrastination will hinder your progress.
Practice Actively (Don’t Just Read) Examples and Online Problems:
Tip: Treat multiple-choice problems as “show-your-work” problems. Solve them step by step, then select the correct answer based on your reasoning. For the online practice exercises, only click the “answer” button after completing your work. Use these resources wisely and responsibly.
Use ISLA to verify your work and ensure accurate statistical reasoning. If your answers differ from the app’s, carefully review your work to identify mistakes. This process helps debug your thinking and strengthens your understanding.
If you struggle with certain concepts or examples, note them down and reach out to me or the excellent tutors at the MLC. Remember: You can succeed regardless of your prior math experience. Challenges are a normal part of learning—don’t hesitate to ask me, tutors, or peers for help. Never give up!
Course policies and expectations for exams are outlined in the syllabus which is posted on the course web page (link is on the top navigation panel).
I provide comprehensive lecture notes and have developed 17 interactive statistics learning apps specifically for this course. Therefore, you do not need to purchase any additional materials or devices. All you need is a commitment to studying the weekly materials and practicing problems through the online exercises.
Other sections of this course may require the textbook Elementary Statistics by Navidi and Monk (3rd edition). However, this class does not require any textbook. I will provide all necessary material through my lecture notes, which follow the same notational system.
If you would like to keep a copy of the textbook for reference, you are welcome to do so. If you do not need it, you must opt out of the required eBook. Once you receive the email notification, be sure to take action—otherwise, you will be automatically charged for the electronic textbook.
I have dedicated significant effort to creating a variety of graphics in the lecture notes and eBook to help you visualize the material wherever possible. Additionally, I’ve developed interactive apps ISLA that complement the topics covered in the notes. These apps are organized as standalone sections under the Use of Technology heading to further deepen your understanding of the content.
Graphing calculators are not required for this
class, as we only use them occasionally for simple
calculations. Instead, you should have a basic scientific
calculator capable of performing the four basic operations
(+, -, ×, ÷) and square roots (\(\sqrt{x}\)).
You can also use the ISLA apps as a statistical calculator—both to verify your manual calculations and to check results in the lecture examples (which is how I use them in class).