INFO-2301: Quantitative Reasoning

Spring 2019, University of Colorado Boulder


Instructor: Prof. Michael Paul (Office hours: Tuesday/Thursday 1:00-2:15, TLC 266)
Canvas: https://canvas.colorado.edu/courses/26226 (check for announcements, assignments, etc.)
Textbook: Diez, Barr, Çetinkaya-Rundel (2015) OpenIntro Statistics, 3rd Edition.
Introduces methods for quantifying and analyzing different types of data, covering foundational concepts in discrete mathematics, probability, and predictive modeling, along with complementary computational skills to apply these concepts to real problems. Covers counting and combinatorics, set theory, introductory probability, common probability distributions, and regression. Requires demonstrated proficiency with introductory computer programming. machine learning
Prerequisites:
Schedule
Policies
Lecture Materials Readings
Weeks 1-6: Data Types and Operations
Monday, January 14, 2019
Introduction
Course overview. Uncertainty and prediction. 		[slides]
[syllabus]
Wednesday, January 16, 2019
Data types and structures
Basic variable types, discrete vs continuous. Vectors and sets. 		[notebook]
Friday, January 18, 2019
Data types and structures
Manipulating lists and sets in Python. Arrays and matrices. 		[notebook]
Monday, January 21, 2019
No class – Martin Luther King Jr. Day
Wednesday, January 23, 2019
Vectors
Notation and terminology. Points, magnitude, distance. 		[notes]
Friday, January 25, 2019
Vector operations
Summation vs addition. Dot product and cosine similarity. 		[notebook]
[notes1]
[notes2]
Monday, January 28, 2019
Mathematical typesetting
Latex and Markdown in Jupyter. 		[notebook]
[notes]
Wednesday, January 30, 2019
Vector operations
Application: ranking by similarity. 		[notebook]
[notes]
Friday, February 1, 2019
Vector operations
More practice with vectors. 		[slides]
Monday, February 4, 2019
Sets
Notation and terminology. Subsets and cardinality. 		[notebook]
[notes1]
[notes2]
Wednesday, February 6, 2019
Set operations
Union, intersection, difference, complement. 		[notebook]
[notes1]
[notes2]
Friday, February 8, 2019
Set operations
Enumerating sets. Algorithmic implementation of set operations. 		[notebook]
Monday, February 11, 2019
Set operations
More practice with sets. 		[notebook]
Wednesday, February 13, 2019
Booleans
Notation and terminology. Boolean variables and logic. 		[notebook]
[notes]
Friday, February 15, 2019
Boolean operations
Generating truth tables. 		[notebook]
[notes1]
[notes2]
Monday, February 18, 2019
Boolean operations
More practice with booleans. Boolean operations as set operations. 		[notebook]
[slides]
Wednesday, February 20, 2019
Introduction to databases
Matrix/vector representation of data tables. Relational databases. 		[notes1]
[notes2]
Friday, February 22, 2019
Database operations
Brief introduction to structured query language (SQL). Practicing boolean operations in database queries. 		[BigQuery1]
[BigQuery2]
[BigQuery3]
Monday, February 25, 2019
Database operations
Practicing set operations in database joins. 		[query]
[notes1]
[notes2]
Weeks 7-13: Discrete Probability and Simulation
Wednesday, February 27, 2019
Random variables
Probability concepts and terminology. 		[slides]
[notes1]
[notes2]
[notes3]
Friday, March 1, 2019
Random variables
Expected value. 		[notebook]
Monday, March 4, 2019
Simulation
Sampling random values. 		[notebook]
[notes1]
[notes2]
Wednesday, March 6, 2019
Simulation
Pseudorandom number generation. 		[notebook]
[notes]
Friday, March 8, 2019
Simulation
Practice with generating pseudorandom values. 		[notebook]
Monday, March 11, 2019
Events
Random outcomes as sets. Addition and multiplication rules. 		[notebook]
[notes]
Wednesday, March 13, 2019
Events
Independence.
Friday, March 15, 2019
Events
Joint distributions and marginalization. 		[notebook]
[notes1]
[notes2]
Monday, March 18, 2019
Conditional probability
General multiplication rule. 		[notebook]
[notes1]
[notes2]
Wednesday, March 20, 2019
Conditional probability
Review: joint, marginal, conditional probabilities. 		[notes1]
[notes2]
Friday, March 22, 2019
Conditional probability
Application: generating music. 		[notebook]
[notes1]
[notes2]
Monday, March 25, 2019
No class – Spring Break
Wednesday, March 27, 2019
No class – Spring Break
Friday, March 29, 2019
No class – Spring Break
Monday, April 1, 2019
Review Day
Practice problems. 		[notes1]
[notes2]
[notes3]
[notes4]
Wednesday, April 3, 2019
Review Day
Practice problems. 		[notes1]
[notes2]
Friday, April 5, 2019
Midterm Exam
Monday, April 8, 2019
Bayes' theorem
Review rules of conditional probability and marginalization. 		[notes]
Wednesday, April 10, 2019
Bayes' theorem
Practice problems. 		[notes1]
[notes2]
[notes3]
Friday, April 12, 2019
Bayes' theorem
Application: spam classification. 		[notebook]
[data]
Weeks 14-16: Combinatorics and Count Distributions
Monday, April 15, 2019
Combinatorics
Introduction. Examples of combinations vs permutations. 		[notebook]
[notes]
Wednesday, April 17, 2019
Permutations
Explanations and formulas. 		[notes1]
[notes2]
[notes3]
Friday, April 19, 2019
Combinations
Explanations and formulas. 		[notebook]
[notes]
Monday, April 22, 2019
Combinatorics
Review and practice.
Wednesday, April 24, 2019
Binomial distribution
Definition and examples. 		[notebook]
[notes]
Friday, April 26, 2019
Binomial distribution
Formulas and practice. 		[notes1]
[notes2]
[notes3]
Monday, April 29, 2019
Review Day
Practice problems. 		[notes1]
[notes2]
Wednesday, May 1, 2019
Review Day
Practice problems. 		[notes]
Friday, May 3, 2019
No class – Last day of classes is Thursday, May 2
Week 17: Final Exam Period
Tuesday, May 7, 2019
Final Exam
4:30pm–7:00pm in MUEN E113 (standard location)
  • Study Guide
  • Extra office hours:
    Monday May 6, 1-4pm, TLC 266