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An Introduction to Python Jupyter Notebooks for College Math Teachers
1. PREFACE
1.1. JMM 2023
1.2. JNB LAB: Patterns
1.3. JNB Lab Solutions
2. PRE-COLLEGE
2.1. Introduction
2.2. Elementary Blackboard Problems
2.3. Beginning Python Programming
2.4. Glimpse of Chicago
2.5. Arts in STEM (STEAM)
2.6. Solution to Exercises
2.7. JNB LAB: After-School Program Demo
2.8. JNB Lab Solutions
3. PYTHON PROGRAMMING GUIDE - Thomas VanDrunen, Yiheng Liang
3.1. Introduction
3.2. Introduction to Python
3.3. Working with Data
3.4. Solution to Exercises
3.5. JNB Lab: Introduction to Python
3.6. JNB Lab Solutions
4. EXPLORATORY DATA ANALYSIS - Wheaton College Team
4.1. The Great Migration
4.2. The Chicago Hardship Index
4.3. Solution to Exercises
4.4. JNB Lab
4.5. JNB Lab Solutions
5. PROBABILITY - Laura Gross, Yiheng Liang
5.1. Introduction
5.2. Random Numbers
5.3. Probability
5.4. Conditional Probability
5.5. Probability Distributions
5.6. Random Walks
5.7. Agent-based Models
5.8. Mathematical Games
5.9. Solution to Exercises
5.10. JNB Lab Homicides in Chicago
5.11. JNB Lab Solutions
6. STATISTICAL INFERENCE - Peter Jantsch, Claire Wagner
6.1. Introduction and Instructor Notes
6.2. Foundations of Statistical Inference
6.3. Hypothesis Testing for Categorical Data
6.4. Hypothesis Testing for Numerical Data
6.5. Linear Regression
7. APPLIED CALCULUS FOR DAILY LIFE - Wheaton College Team
7.1. Introduction
7.2. Linear Systems and the Two-commodity Model
7.3. Marginal and Average Cost
7.4. Optimization and Object Design
7.5. Optimization and Cobbs-Douglas Production
7.6. Related Rates and Volumes
7.7. Related Rates with Trig Functions and Football
7.8. Probability Distributions and Drive Thrus
7.9. Normal Distribution and Process Control
7.10. Partial Derivatives and OLS Regression
7.11. Area Between Curves and the Gini Index
7.12. Integral Test and Income Streams
7.13. Ordinary Differential Equations and Exponential Growth/Decay
7.14. Solutions to Exercises
7.15. JNB Lab: Calculus of Entropy in Daily Life and Monte Carlo Simulations
7.16. JNB Lab Solutions
8. CALCULUS - Inne Singgih
8.1. Introduction
8.2. Functions
8.3. Limits, Continuity, and Rates
8.4. Derivatives
8.5. Integrals
8.6. Parametric Equations
8.7. Sequences and Series
8.8. Solution to Exercises
8.9. JNB LAB: Calculus Animations
8.10. JNB Lab Solutions
9. LINEAR ALGEBRA - Soheil Anbouhi
9.1. Introduction
9.2. Linear Systems
9.3. Matrices and Determinants
9.4. Linear Transformations
9.5. Eigenvalues and Eigenvectors
9.6. Orthogonality
9.7. Solutions to Exercises
9.8. Linear Algebra Lab
9.9. Linear Algebra Lab Solutions
10. LINEAR ALGEBRA AND OPTIMIZATION FOR DATA ANALYSIS - Wheaton College Team
10.1. Introduction
10.2. OLS Linear Regression
10.3. K-means Clustering
10.4. Dimension Reduction by Principal Component Analysis
10.5. Binary Classification of Labelled Data by Support Vector Machines
10.6. Solution to Exercises
10.7. JNB LAB: Linear Algebra for Data Analysis
10.8. JNB Lab Solutions
11. DIFFERENTIAL EQUATIONS - Rachel Petrik
11.1. Overview of Chapter
11.2. Introduction to Differential Equations
11.3. First-Order Differential Equations
11.4. Second-Order Differential Equations
11.5. Systems of First-Order Differential Equations
11.6. Laplace Transforms
11.7. Solutions to Exercises
11.8. Differential Equations Lab
11.9. Differential Equations Lab Answer Key
12. DIFFERENTIAL EQUATIONS FOR THE BENEFIT OF SOCIETY - Wheaton College Team
12.1. Introduction
12.2. Logistic Growth and COVID-19
12.3. The Basic SIR Model
12.4. Cholera in Haiti
12.5. CWS Model of Alzheimer’s Disease
12.6. Gravity Fed Water Delivery
12.7. Earthquake Resistant Construction
12.8. Solutions to Exercises
12.9. JNB Lab: HIV-AIDS
12.10. JNB Lab Solutions
13. COMPLEX VARIABLES IN GROUNDWATER MODELING - Wheaton College Team
13.1. Setting the Scene
13.2. Complex Analysis Background
13.3. Idealized Groundwater Flow
13.4. Contaminant Extraction Modeling
13.5. Solutions to Exercises
13.6. JNB LAB: Complex Potentials and Contaminant Flow
13.7. JNB Lab Solutions
14. ADVANCED DATA ANALYSIS - Ying Li, Jonathan Zhu, Claire Wagner
14.1. Before Reading
14.2. Preprocessing
14.3. About Text Data
14.4. Document Embedding
14.5. Classification of Texts
14.6. Evaluating Classification
14.7. Applications
14.8. Solutions to Exercises
15. COMPLEX SYSTEMS - Wheaton College Team
15.1. Introduction
15.2. Fundamental Concepts
15.3. Mathematical Concepts from Equilibrium Statistical Physics
15.4. Societal Applications
15.5. Solution to Exercises
15.6. JNB LAB: Complex Systems
15.7. JNB Lab Solutions
Index
Repository
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PYTHON PROGRAMMING GUIDE - Thomas VanDrunen, Yiheng Liang
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PYTHON PROGRAMMING GUIDE - Thomas VanDrunen, Yiheng Liang
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