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Introduction to R Studio: Thinking & Analyzing Data for Real World Decision Making

Contact Information
Adolph “AJ” Delgado, Ph.D., M.Ed., M.S.
HCAP Postdoctoral Fellow
Email:

Course Start Date

Workshop Description

This workshop is designed to equip participants with the essential skills and knowledge needed to work with administrative health data using R and leverage ChatGPT for natural language interaction. Students will learn to access, clean, manipulate, analyze health data, create R Markdown reports for publication on Rpubs, and use ChatGPT for data-related discussions and assistance.

Objectives

By the course’s end, students will:

  1. Access and retrieve administrative health data.
  2. Filter and select relevant data variables.
  3. Manipulate data structures efficiently.
  4. Describe data using statistics and visualizations.
  5. Analyze health data through appropriate methods.
  6. Interpret and communicate data-driven insights.

Required Software

For this course, the required software includes:

  • Required for data analysis in R.
  • R Packages: Necessary for data manipulation, visualization, and analysis.
  • Rpubs Account: Needed for publishing reports.
  • ChatGPT Access: For interactive discussions.
  • Data Sources: Access to relevant datasets.

In person Meeting Time & Place

1PM @ Main Campus

Online Meeting Time

Adolph Delgado is inviting you to a scheduled Zoom meeting.

Topic: R Workshop Time: Apr 5, 2024 01:00 PM Central Time (US and Canada) Every week on Fri, until Jun 7, 2024, 10 occurrence(s) Apr 5, 2024 01:00 PM Apr 12, 2024 01:00 PM Apr 19, 2024 01:00 PM Apr 26, 2024 01:00 PM May 3, 2024 01:00 PM May 10, 2024 01:00 PM May 17, 2024 01:00 PM May 24, 2024 01:00 PM May 31, 2024 01:00 PM Jun 7, 2024 01:00 PM Please download and import the following iCalendar (.ics) files to your calendar system. Weekly: https://utsa.zoom.us/meeting/tJwtfuisrjgoHN1gUCoO7HRFuhNKAMBdKeoZ/ics?icsToken=98tyKuCgrjIrHtSWsh-ORow-Aor4d-jziHZBgo0MmyrGDA8ESjHQI-psGZNSMtz7

Join Zoom Meeting https://utsa.zoom.us/j/98091403269

Meeting ID: 980 9140 3269

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Meeting ID: 980 9140 3269

Find your local number: https://utsa.zoom.us/u/aelDKlVyPR

Please note the following steps when contacting me:

  • Make sure to thoroughly review the syllabus, announcements, and recorded lectures before sending me an email: sometimes the answer is already available to you.

  • When sending me an email, include BOTH the workshop name (i.e., R Workshop) and your full name (e.g., First Last) in the subject line.

  • In all communications, be specific. I will not reply to an email that says, “How do you analyze the data?”. Alternatively, I will reply to an email that says, “I watched the lecture and understand that I need to calculate a linear regression on HIV prevalence by race. But, the model is showing an error. Please see the attached screenshot.”

  • In each email, professional and respectful language is expected.

  • I check my email regularly from Monday to Friday from 8am to 5pm. Within that timeframe, I will generally respond within 24 hours. If you do not hear back from me, send another email in the event that your message went to my Junk email box.

  • On the weekends, I am generally not available by email, but will reply on the subsequent Monday. If you need to contact me, plan ahead.

Schedule

Week 1: Introduction to Health Data Analysis and RStudio

  • Objectives:
    • Provide an overview of the significance of health data analysis in research and practice.
    • Familiarize participants with the RStudio environment.
    • Demonstrate data import techniques.

Week 2: Data Import and Cleaning

  • Objectives:
    • Importing various health data formats.
    • Emphasize the importance of data cleaning for accurate analysis.

Week 3: Data Manipulation and Filtering

  • Objectives:
    • Enable efficient manipulation of data structures.
    • Teach techniques for filtering and selecting relevant variables.

Week 4: Data Description and Summarization

  • Objectives:
    • Describe data using appropriate descriptive statistics.

Week 5: Data Description and Summarization

  • Objectives:
    • Analyze health data through descriptive methods.

Week 6: Statistical Analysis of Differences in Health Data

  • Objectives:
    • Analyze and Interpret differences in health data.

Week 7: Statistical Analysis of Relationships in Health Data

  • Objectives:
    • Analyze and Interpret relationships in health data.

Week 8: Visualization of Health Data

  • Objectives:
    • Create visual representations of health data.

Week 9: Apply Skills to Analyze Health Data

  • Objectives:
    • Engage in real-world health data analysis projects.

Week 10: Workshop Wrap-Up

  • Objectives:
    • Final thoughts and reflections.