This website was last updated on Sunday, August 23, 2026.
Fall 2026 Syllabus
  • Syllabus is updated at the end of the most recent completed semester.

Contact Information: Professor Pooler (pspooler@syr.edu) - Office: WSOM Room 518
NOTES:

  • This is the permanent version of Professor Pooler’s MAS 261 Course Website and is only updated at the end of the semester or when substantial changes are made to the material during the semester.

  • Homework assignments and ‘Practice Questions’ for tests are not posted on the permanent MAS 261 Website.

  • Lectures that are solely devoted to review and preparation for mid-semester tests and the final exam are also not available on the permanent website.

    • Missing lecture numbers are associated with review lectures and in-class test days.
Read this letter about AI

  • Using AI in coding and writing is commonplace and helpful if used cautiously and ethically.

  • This is a great ‘letter’ from a high school student who ‘broke up’ with AI because she felt it was supplanting her own voice. It’s worth your time to read and consider it.

Useful Software Links OPTIONAL Software Training
  • DataCamp
    • An excellent (but not free) online learning center for many software packages. Costs can be subsidized (see below).

  • Whitman WIRE Initiative

    • The WIRE initiative will subsidize costs of online software training that results in certification.

    • Contact their office to arrange a meeting and develop a plan.


  • SU Open Source Program Office (OSPO)
    • OSPO offers workshops in open source software such as R/RStudio, Python, Github and facilitates communication between open source software users on campus.
Estimates and Confidence

  • Lecture 14 - Effect of Sample Size and Confidence level on Confidence Intervals

  • Lecture 13 - Intro. to the t Distribution and Confidence Intervals

Data Distributions

  • Lecture 8 - Sampling Distribution of the Sample Mean / CLT

  • Lecture 7 - Empirical Rule / Finding X from a Probability

  • Lecture 6 - Introduction to the Normal Distribution

Describing Data
  • Lecture 5 - Visualizing Categorical and Quantitative Data

  • Lecture 4 - Data Visualizations, Boxplots, Outliers





Linear relationships
  • Lecture 27 - Introduction to Linear Transformations



  • Lecture 24 - Introduction to Simple Linear Regression


Hypotheses and Correlations
  • Lecture 20 - Introduction to Correlation and Covariance


  • Lecture 18 - Two Sample t-Tests and Confidence Intervals

  • Lecture 17 - Language of Hypothesis Testing/One Sample t-tests
Notes

  • Students in MAS 261 are NOT required to install R and RStudio on their laptop but they are welcome to.

  • R and RStudio are two separate software components. Download and install R and then download and install RStudio.

  • When updating your version of R or RStudio, uninstall the previous version first.

Downloading and Installing R
Downloading and Installing RStudio

  • RStudio can be downloaded from Posit, the parent company of RStudio.

  • Video Demo for downloading and installing RStudio on a Windows OS

  • Mac installation is similar.

  • If you do not need to uninstall an out-of-date version of RStudio, skip to 0:56.

  • The version shown in the video is from August of 2024 and is out-of-date.

  • The current version of RStudio is 2026.8.1.195, which was published on August 18, 2026.