MAT 241: Introduction and What to Expect

Dr. Gilbert

January 8, 2026

What Are We Here For?

Location Loc Population MedianAgeMarriage Marriage Marriage SE Divorce Divorce SE WaffleHouses South Slaves1860 Population1860 PropSlaves1860
Alabama AL 4.78 25.3 20.2 1.27 12.7 0.79 128 Southern State 435080 964201 0.45
Alaska AK 0.71 25.2 26.0 2.93 12.5 2.05 0 Other State 0 0 0.00
Arizona AZ 6.33 25.8 20.3 0.98 10.8 0.74 18 Other State 0 0 0.00
Arkansas AR 2.92 24.3 26.4 1.70 13.5 1.22 41 Southern State 111115 435450 0.26
California CA 37.25 26.8 19.1 0.39 8.0 0.24 0 Other State 0 379994 0.00
Colorado CO 5.03 25.7 23.5 1.24 11.6 0.94 11 Other State 0 34277 0.00

We’ll ask questions and use data to investigate their answers.

What Are We Here For?

We’ll ask questions and use data to investigate their answers.

Territory Bands Population Happiness
Afghanistan 2 37466414 2.404
Albania 7 3088385 5.199
Algeria 16 43576691 5.122
Andorra 2 85645 NA
Angola 8 33642646 NA
Argentina 1907 45864941 5.967

Syllabus

Major Highlights from the Syllabus: I’ll ask you to read the syllabus, but the most important items are on the following slides.

Instructor and Office Hours

  • Instructor: Dr. Adam Gilbert

    • E-mail Address: a.gilbert1@snhu.edu

    • Office: Robert Frost Hall, Room 311

    • Drop-In Office Hours (please visit!):

      • Wednesdays 1:00pm - 2:00pm
      • Thursdays 9:00am - 11:00am
      • Fridays 9:00am - 11:00am

Class Embedded Tutor

  • Embedded Tutor: Brent Zukowski

Required Resources

First and foremost…everything is free!

Grading Scheme

Grade Item Value
Participation 10%
Interactive Notebooks (~17) 20%
Exams (2) 50%
Final Exam (two parts) 20%

Explanations of Grade Items

  • Interactive Notebooks: Completing these on time is crucial, as they’ll be the way you are exposed to material and practice with it.

    • You should expect to have one due prior to nearly every class meeting.
    • You’ll generate a hash code at the end of each notebook and submit that hash code using a Google Form (see BrightSpace for the link)

  • Exams: We’ll have two exams during the semester – each one will have three parts.

    • Group Exam (Practice): First meeting of exam week, random groups, can count for up to 10% of exam score but cannot hurt you.
    • Individual Exam (75% 0r 65%): Similar to the group exam, but you’re on your own this time.
    • Practical Exam (25%): You’ll work with a real data set and perform a scripted analysis using R/RStudio and building a Quarto Document.

  • Final Exam: The final exam will also come in two parts.

    • Part A (Required): Covers statistical inference (approximately the later two-thirds of the semester).
    • Part B (Optional): Covers descriptive statistics and probability (approximately the first third of the semester).

Brightspace

  • Announcements
  • Gradebook
  • Go to the webpage for everything else

Course Webpage

I’ve built a webpage to organize our course content.

  • Syllabus

  • Tentative timeline

    • Weekly discussion topics and required interactive notebooks
    • Optional supplementary discussion slides
    • Assignment due date reminders

What’s Class Like?

  • There are a couple of options and you’ll dictate which one we’ll take on a daily basis.

    • I’ve built this course to make lecture optional – If you’re feeling comfortable with the content from the interactive notebook for the day, we’ll examine a real data set, exploring those topics you were exposed to in the notebook.
    • If you feel like your grasp on content is weak, then we’ll have a more lecture-based class discussion, covering the content in detail.
    • Of course, a combination of these approaches is certainly possible as well.

  • In a math / statistics course, seeking help immediately is critical – please do not wait until the next class meeting to get your question answered.

    • Depending on your level of preparation, you should expect to spend 3 to 6 (or more) hours per week on this course outside of class time.

A Note on AI Use

The use of AI, such as chatGPT or copilot, in MAT241 will be discussed in class, particularly prior to exams.

  • While AI will not be completely prohibited, its use will generally be restricted to helping with broken code in R.
  • The reason for taking this position is that MAT241 is a foundational course in which we are learning and applying concepts from applied statistics.
  • Relying on AI for statistical calculations and interpretations at this stage will rob you of the opportunity to understand and discover the intricacies involved in statistical analysis.

Previewing Use of AI in MAT241: AI use is permitted only for troubleshooting code you’ve written.

  • In the case that AI is used, please plan to save and provide your transcript along with your submission.
  • If AI use is suspected and a transcript is not provided on request, then an academic integrity inquiry will be submitted via the University’s formal channels and an investigation will determine the outcome.

A Road Map to Our Semester

We’ll be discussing a lot of material in MAT 241. Here is a very generic road map of what we will discuss. Starting now.

  • Introduction to Data

  • Introduction to R

  • Descriptive Statistics (Exploratory Data Analysis, EDA)

    • Numerical and tabular summary statistics
    • Data visualization
    • Interpretations and communications of EDA

  • Just Enough Probability

    • Binomial Distribution
    • Normal Distribution

  • Inferential Statistics

    • Confidence intervals for capturing a population parameter
    • Hypothesis tests for testing claims about a population parameter

  • Contexts

    • Single means or proportions
    • Comparisons of means or proportions across two or more groups
    • Associations between a numerical variable and one or more other variables numerical variables (linear regression)

Software Setup

It’s important to get the software set up for this course so that we can hit the ground running. In most cases, this is pretty seamless, but there are always a few instances where the setup requires troubleshooting.

If worst comes to worst, you will be able to use Posit Cloud to complete all of the work for this course. I have a pre-built workspace that you can copy. The downside is that your access time is limited to 25 hours per month.

We’ll use this time to get interactive notebooks up and running. This is a three-step process, documented with links here. A general description of the steps appears below. I’ll skip to the Exit Ticket slide so that people with complete setups can finish that and take back some of their time.

  1. Download and install the R computing language
  2. Download and install RStudio
  3. Install the R package containing the interactive notes for our course.

Exit Ticket Task

Navigate to our MAT241 Exit Ticket Form, answer the questions, and complete the task below.


Note. Today’s discussion is listed as 0. Introduction and What to Expect

Task: Tell me one interesting thing about you. Additionally, please share any questions, comments, or concerns you have as we embark on our MAT241 journey together. You should know that I’m looking forward to working with you and getting to know you!

Closing

  1. Render your notebook and make sure that the sections we’ve updated look as you intended them to.

    • Make any updates you like and re-render the notebook.

  2. We got a first taste of R today, and we’ll continue to learn more.

  3. Don’t worry if you didn’t completely understand all of the code from today’s Quarto Document or if you feel like you couldn’t write that code on your own – we’ll be starting from scratch!

  4. Homework: Complete and submit the Topic 1 notebook at least 30 minutes before our next class meeting. These notebooks will give you a first introduction to data and R, respectively.

    • Be sure to see me immediately if you are having difficulty with setup.