BUA 345
  • This website provides PERMANENT access to BUA 345 lecture slides, notes, and R code files, regardless of access to Blackboard.
  • Syllabus and Course Links
  • Lectures 1-8
  • Lectures 9-18
  • Lectures 20-27
  • Installing R and RStudio
  • Interesting Data
This website was last updated on Saturday, January 10, 2026.
Spring 2025 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 BUA 345 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 BUA 345 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
  • Posit Cloud
  • R
  • RStudio
  • Quarto
  • RPubs
OPTIONAL Software Training
  • LinkedIn Learning - Free for Syracuse University Students, Staff, and Faculty

    • R for Data Science: Analysis and Visualization - This training is optional and provides a good introduction to R and RStudio which are used in this course.

    • Python Essential Training - Python is not used in this course but it is helpful for analytics and data science.


  • 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.
Instructions for Downloading and Saving Excel Files:
  1. Create a BUA 345 folder on your laptop’s Desktop.

    • NOTE: If you are on a campus computer, when you login, the desktop is connected to your ‘Syracuse University OneDrive’ and can be opened on SU computer when you login with your NetID and Password.
  2. Click link below to open file, then click File > Download > Microsoft Excel (.xlsx)

  3. Move file from Downloads to your Desktop BUA 345 folder.


Excel Skills and Simple Linear Regression (SLR) Review
  • MAS 261
    • Helpful Lectures from MAS 261 - Fall 2025
      • Lecture 17 - Language of Hypothesis Testing/One Sample t-tests
      • Lecture 20 - Introduction to Correlation and Covariance
      • Lecture 24 - Introduction to Simple Linear Regression
      • Lecture 25 - Simple Linear Regression Continued
      • Lecture 26 - Multiple Linear Regression
      • Lecture 27 - Introduction to Linear Transformations
    • Recordings of these lectures are available upon request.

Poll Everywhere

My User Name: penelopepoolereisenbies685


BUA 345 Student R Files for Lectures 7-18 - R Project on Posit Cloud - Click link to open file in your Posit Cloud and save it. Once file is saved to your account, you should not click this link again.


Review of Simple Linear Regression
  • Lecture 8 - Introduction to Regression Modeling in R
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

  • Lecture 7 - Introduction to R/Rstudio in Posit Cloud and Review of Correlation
    • Slides
    • Notes
    • PDF
    • Excel Files - Download to a BUA 345 folder on your desktop:

      • Lecture 7 Review Question Data.xlsx
    • Posit Cloud
      • Your saved file with your work will be in your account.

Excel Skills
  • Lecture 6 - Data Queries
    • Slides
    • Notes
    • PDF
    • Excel Files - Download to a BUA 345 folder on your desktop:

      • Lecture 6 Excel Worksheets.xlsx

  • Lecture 5 - Descriptive Analytics with Pivot Tables Cont’d
    • Slides
    • Notes
    • PDF
    • Excel Files - Download to a BUA 345 folder on your desktop:

      • Lecture 5 Review Question Data.xlsx
      • Lecture 5 Excel Worksheets.xlsx

  • Lecture 4 - Descriptive Analytics with Pivot Tables
    • Slides
    • Notes
    • PDF
    • Excel Files - Download to a BUA 345 folder on your desktop:

      • Lecture 4 Review Question Data.xlsx
      • Lecture 4 Excel Worksheets.xlsx
    • Posit Cloud Demo - Titanic Data - Click links

      • HTML file
      • R Project
        • Free Posit Cloud Account Required

  • Lecture 3 - Data Preparation and Conditional Formatting
    • Slides
    • Notes
    • PDF
    • Excel Files - Download to a BUA 345 folder on your desktop:

      • Lecture 3 Review Question Data.xlsx
      • Lecture 3 Excel Worksheets.xlsx

  • Lecture 2 - Data Preparation in Excel
    • Slides
    • Notes
    • PDF
    • Excel Files - Download to a BUA 345 folder on your desktop:

      • Lecture 2 Review Question Data.xlsx
      • Lecture 2 Excel Worksheets.xlsx

  • Lecture 1 - Welcome and Introduction to Business Analytics
    • Slides
    • Notes
    • PDF
    • Excel Files - Download to a BUA 345 folder on your desktop:

      • Big_Mac_Index.xlsx
Regression Modeling
  • Lecture 18 - Logistic Regression
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.
    • Lecture 18 Excel Worksheets
      • Titanic_Betas and Model Worksheet.xlsx
      • Late_Payment_Betas Model Worksheet.xlsx

  • Lecture 17 - More about Model Selection
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

  • Lecture 16 - Introduction to Model Selection Continued
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.
    • Animal_Worksheets.xlsx

  • Lecture 15 - Introduction to Model Selection
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

  • Lecture 14 - Categorical Regression - Interaction Model
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

  • Lecture 13 - Categorical Regression - Parallel Lines Model
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

  • Lecture 10 - Multiple Linear Regression Models in R
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

  • Lecture 9 - More about Linear Regression Models in R
    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

Forecasting

BUA 345 Student R Files for Lectures 25, 26 and HW 10 - R Project on Posit Cloud - Click link to open file in your Posit Cloud and save it.Once file is saved to your account, you should not click this link again.


  • Lecture 27 - Stock Dashboard

    There is a very short in-class exercise on Blackboard associated with this in-class activity. This will count for today’s class particpation. No Blackboard submissions for this exercise will be accepted after midnight on Wednesday, 4/23.

    • Example Dashboard
      • View in full-screen mode.

  • Lecture 26 - Forecasting - Part 2

    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

  • Lecture 25 - Introduction to Forecasting

    • Slides
    • Notes
    • PDF
    • Posit Cloud
      • Your saved file with your work will be in your account.

Non-Linear Models and Optimization
  • Lecture 24 - Linear and Integer Programming
    • Slides
    • Notes
    • PDF
    • Lecture 24 Excel File
      • Lecture 24 - Excel Worksheets - Linear and Integer Programming.xlsx
      • Lecture 24 - Excel Worksheet - Cookie Question with updated Supply and Demand.xlsx

  • Lecture 23 - Introduction to Unconstrained Optimization
    • Slides
    • Notes
    • PDF
    • Lecture 23 Excel File
      • Lecture 23 - Excel Worksheets - Unconstrained Optimization using Excel Solver.xlsx
      • Lecture 22 - Three Data Sets and Plots (with some solutions).xlsx

  • Lecture 22 - Introduction to Non-Linear Models
    • Slides
    • Notes
    • PDF
    • Optional R Project for Lecture 22
    • OPTIONAL R Project HTML File
    • Lecture 22 Excel Files
      • Lecture 22 - Three Data Sets and Plots (without trendlines).xlsx
      • Lecture 22 - Three Data Sets and Plots (with some solutions).xlsx

Notes
  • Students in BUA 345 are NOT required to install R and RStudio on their laptop but they are encouraged 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
  • R can be downloaded from the Comprehensive R Archive Network

  • Video Demo for downloading and installing R on a Windows OS
  • Mac installation is similar.

  • If you do not need to uninstall an out-of-date version of R, skip to 0:53.

  • The current version of R is 4.5.2.


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 2026.1.0.392.

NOTES:
  • Many data sources provide data in a downloadable format such as Excel (.xlsx) or .csv. I recommend saving data as CSV UTF-8 files with a .csv postscript.

  • The list below is in alphabetical order and is not an exhaustive list.

  • Some data sources do not provide data in a downloadable format so the data values have to be scraped from the website.

Billboard
  • Scraping required
BEA - Bureau of Economic Analysis
BLS- Bureau of Labor Statistics
Box Office Mojo
  • Scraping required but it’s straightforward.
Competence Centre on Composite Indicators and Scoreboards
  • Great source for unusual datas
Data World
  • An ecclectic library of data that can be searched by topic of interest
Department of Energy - Prices & Trends
Eurostat
  • A wide variety of data about Europe can be accessed at this site.

  • Aanalogous to US.Gov for the United States.

Federal Reserve Data
Kaggle
  • An ecclectic library of data that can be searched by topic of interest
  • Kaggle also holds competitions where data scientists can win money and build a reputation
Our World in Data
  • Good source for geographic and demographic data
Sports Reference
  • Scraping required
  • Wide range of sports data
Statista
  • Syracuse University Libraries provides paid membership access
  • Use link above and then sign in with SU NetID and Password
  • Excellent resource for public and private sector data
U.S. Energy Information Administration
  • Excellent information on electricity usage by location or region.
Data.Gov - Data and Statistics about the U.S.
  • Includes MANY topics including BLS, DOE, and EIA above
Yahoo Finance
  • Stock data can be directly imported into R as an xts dataset