DANL 101 · Fall 2026 · SUNY Geneseo
Learn to think with data.
Analyze data with R, create clear visualizations, and tell evidence-based stories that help people decide—with generative AI supporting the process.
Everything in reach
Course materials
Find the available lecture slides, classwork, and homework below. Weekly pages show how the materials fit together.
Lecture slides
- Lecture 1 Syllabus and Course Outline
- Lecture 2 Data Analytics Thinking and Tools
- Lecture 3 R Fundamentals
- Lecture 4 Descriptive Statistics with R
- Lecture 5 Reading and Transforming Data with R
- Lecture 6 Data Types, Databases, and Keys
- Lecture 7 Data Visualization I: Distributions and Group Comparisons
- Lecture 8 Data Visualization II: Relationships and Time Trends
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Classwork
- Classwork 10 Distribution of a Numeric Variable
- Classwork 11 Distribution of a Numeric Variable Across Groups
- Classwork 12 Distribution of a Categorical Variable
- Classwork 13 Distribution of a Categorical Variable Across Groups
- Classwork 14 Exploring Relationships with Scatterplots
- Classwork 15 Seeing Relationships with a Log Transformation
- Classwork 16 Time Trends and a Short Data Story
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Homework
Exams
- Selected Past Exam Questions for Midterm DANL 101 · Fall 2026
- Midterm Exam Guide DANL 101 · Fall 2026
- Midterm Exam Version A: Questions and Answers Grading summary and example answers
- Midterm Exam Version B: Questions and Answers Grading summary and example answers
- Midterm Exam Version C: Questions and Answers Grading summary and example answers
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Dates to keep in view
Plan around the moments that shape the semester.
First course meeting
Fall break
Midterm exam
Group presentations
Semester map
From analytics thinking to data-informed decisions.
Prepare data and study databases before the October 19 midterm, then continue visualization through Week 12. Explore data analytics with AI in Week 13 and apply it to the group project in Week 14 before presentations.
01Frame · Weeks 1–2Analytics questions + decision toolsTurn decisions into answerable questions, evaluate evidence, and use dashboards and analytics tools thoughtfully.→ 02Build · Weeks 3–4R foundations + statisticsWork with objects, vectors, data frames, and functions, then summarize center, spread, and distributions.→ 03Prepare · Weeks 5–8Statistics, transformation + databasesSummarize data, practice dplyr, and use Lecture 6 to understand data types, relational tables, keys, and left_join().→ 04Assess + visualize · Weeks 9–12Midterm + data visualizationAfter the October 19 midterm, move from distributions and group comparisons to relationships and time trends, continuing Lecture 8 in Week 12.→
05DANL + AI · Week 13 · Coming soonData analytics with generative AIStudy capabilities and limits, practice prompting and iteration, and verify analytical outputs while considering disclosure, bias, and privacy.
06Apply + present · Weeks 14–16 · Coming soonProject + AI, then presentationsUse AI selectively in the group project, check data and code, verify and disclose assistance, then refine findings, rehearse, and present.