Math 119 — Applied Calculus for Data Analysis

Today: Class 3

Next class: Class 4 — Friday, Sep 18

This course connects calculus concepts to real-world data analysis using R and Mathematica. You’ll model LED bulb degradation, fit data using maximum likelihood, and analyze probability distributions — building mathematical intuition through hands-on computation.

Getting Started (Week 1)

TipFirst Week Checklist

Before Class 1: 1. Read the Syllabus on Canvas 2. Complete the Background Survey (Canvas) 3. Open KnewtonAlta and try a few questions

Before Class 2: 1. Install R and Positron (our IDE) 2. Plot a simple function in R (see Class 2 prep) 3. Review equation-solving strategies

First Two Weeks: - Work through Example Project to learn the workflow - Start Project 1 (due Week 6)

Course Structure

Class Sessions (46 total)

Daily class pages guide your learning with prep work, in-class activities, and practice problems. Use the Class Sessions sidebar to navigate by day.

Need help finding a topic? Use Help → Topic Index to search by concept (e.g., “chain rule”, “uniroot”, “maximum likelihood”).

Three Major Projects

  1. Project 1: LED Bulb Lifetime (Weeks 1-6) — Function modeling, visual fitting, uniroot
  2. Project 2: Maximum Likelihood (Weeks 7-10) — Derivatives, optimization, calculus-based fitting
  3. Project 3: Probability Distributions (Weeks 11-13) — Integration, expected value, variance

Projects use specifications grading: your work earns “Complete” when it meets all five specs. Revise and resubmit until it does.

Weekly Practice

KnewtonAlta homework reinforces skills. Complete assignments by their due dates to stay on track.

Essential Resources

Get Unstuck

Tools & Guides

Course Calendar

View the full Schedule to see daily topics, exam dates, and holidays.

Questions? Ask on Canvas discussions or visit office hours.