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
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Classwork
- Classwork 1 NYC311 Dashboard - From a visible pattern to a responsible next step
- Classwork 2 R Fundamentals
- Classwork 3 Descriptive Statistics
- Classwork 4 Filtering a Vector
- Classwork 5 Finding and Copying an Absolute Pathname
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Classwork 6
Data Transformation with R -
filter(),arrange(), anddistinct() -
Classwork 7
Data Transformation with R -
select()andrename() - Classwork 8 Taxonomy of Data
- Classwork 9 Combining Tables with left_join()
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Homework
- Homework 1 Data Analytics Thinking, R Fundamentals, and Descriptive Statistics
- Homework 2 Descriptive Statistics and Reading and Transforming Data with R
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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 explore visualization for three weeks and generative AI for two weeks before project work and 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 9–11 · Coming soonMidterm + data visualizationTake the midterm on October 19, then build charts for distributions, relationships, and time trends.
05Explore AI · Weeks 12–13 · Coming soonGenerative AI + responsible useStudy capabilities and limits, practice prompting and iteration, and verify outputs while considering disclosure, bias, and privacy.
06Apply + present · Weeks 14–16 · Coming soonProject studio + presentationsCheck the group project’s data and code, refine findings, rehearse, and present the completed analysis.