Quantitative Reasoning 1: Intuitions and Evidence

Spring 2017, INFO-1301, University of Colorado Boulder


Instructor: Prof. Michael Paul (Office hours: Friday, 10:15am–11:45am, ENVD 207)

Time/Place: MWF 2:00pm–2:50pm
HUMN 1B80

Contact: info1301@colorado.edu

Textbook: Diez, Barr, Çetinkaya-Rundel (2015) OpenIntro Statistics, 3rd Edition.


Surveys concepts and techniques for characterizing and quantifying data. Students will learn to use different types of quantitative data, to summarize data with descriptive statistics, to measure similarity of different datasets, to interpret probabilities and statistical significance and to quantify and predict changes in data.

No prerequisites. 		data, probability, statistics


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Lecture Materials Readings
Part 1: The Shape of Data
Wednesday, January 18, 2017
Introduction
Course introduction and overview. 		[slides-1]
Friday, January 20, 2017
What is data?
Representations and types of data. 		[slides-2]
  • Diez 1.1
  • Diez 1.2.1-1.2.2
Monday, January 23, 2017
What is a data? (cont'd)
Data relationships, associations, correlations. 		[slides-3]
  • Diez 1.2.3
Wednesday, January 25, 2017
What is data? (cont'd)
Representing data with software.
Friday, January 27, 2017
What is a dataset?
Representing collections. Sets, vectors, matrices. 		[slides-4]
Monday, January 30, 2017
What is a dataset? (cont'd)
Collecting data. Populations and sampling. 		[slides-5]
Wednesday, February 1, 2017
What is a dataset? (cont'd)
Practice with collecting and understanding datasets.
Friday, February 3, 2017
Review Day
Catch up and additional practice.
Monday, February 6, 2017
Describing data
Central tendency and variability. 		[slides-6]
Quiz 1 today
  • Diez 1.6
  • Diez 1.7.1-1.7.2
Wednesday, February 8, 2017
Describing data (cont'd)
Visualzing data. Practice with software. 		[slides-6]
Friday, February 10, 2017
Describing data (cont'd)
Interpreting descriptive statistics. 		[slides-7]
Monday, February 13, 2017
Counting data
Introduction to combinatorics. 		[slides-8]
Wednesday, February 15, 2017
Counting data (cont'd)
Understanding combinatorics. Revisiting sampling. 		[slides-9]
Friday, February 17, 2017
Truth and logic
Introduction to boolean variables and boolean logic. 		[slides-10]
Monday, February 20, 2017
Truth and logic (cont'd)
Truth tables and boolean algebra.
Wednesday, February 22, 2017
Truth and logic (cont'd)
Boolean queries. Brief introduction to databases.
Friday, February 24, 2017
Review Day
Catch up. More examples.
Monday, February 27, 2017
Midterm Exam 1
Part 2: Randomness of Data
Wednesday, March 1, 2017
Probability basics
Random variables, outcomes. Why is probability useful? 		[slides-11]
Friday, March 3, 2017
Probability basics (cont'd)
Probability operations, independence. Revisiting sets, Venn diagrams. 		[slides-12]
  • Diez 2.1.3-2.1.6
Monday, March 6, 2017
Probability basics (cont'd)
Practice with probability. Computational simulations.
Wednesday, March 8, 2017
Probability basics (cont'd)
Interpreting probability. 		[slides-13]
Friday, March 10, 2017
Probability basics (cont'd)
More practice.
Monday, March 13, 2017
Data uncertainty
Sampling and measurement error. 		[slides-14]
  • Guide to Data, pages 25-32
    		•
    Wednesday, March 15, 2017
    Review Day
    Catch up. More examples.     		[slides-15]
    Friday, March 17, 2017
    The normal distribution
    Bell curves and the normal approximation.     		[slides-16]
    • Diez 3.1.1-3.1.2
    • Recommended: Freedman 5.1
    Quiz 2 today
    Monday, March 20, 2017
    The normal distribution (cont'd)
    Data standardization. Area and percentiles.     		[slides-17]
    • Diez 3.1.3-3.1.5
    • Recommended: Freedman 5.2-5.4
    Wednesday, March 22, 2017
    Quantifying chance
    Variability, confidence intervals.     		[slides-18]
    • Diez 4.1
    • Diez 4.2.1-4.2.2
    Friday, March 24, 2017
    Quantifying chance (cont'd)
    Central limit theorem.     		[slides-18]
    • Diez 4.2.3-4.2.5
    Monday, March 27, 2017
    No class – Spring break
    Wednesday, March 29, 2017
    No class – Spring break
    Friday, March 31, 2017
    No class – Spring break
    Monday, April 3, 2017
    Quantifying chance (cont'd)
    Practice problems with confidence intervals and z-scores.
    Wednesday, April 5, 2017
    Quantifying chance (cont'd)
    Interpreting confidence intervals and p-values.     		[slides-19]
    Friday, April 7, 2017
    Quantifying chance (cont'd)
    Confidence intervals in software.
    Monday, April 10, 2017
    Review Day
    Catch up. More examples.
    Wednesday, April 12, 2017
    Midterm Exam 2
    Part 3: Changes in Data
    Friday, April 14, 2017
    Rate of change
    Slope and intercept.     		[slides-20]
    • Freedman 7.1-7.3 (available in D2L)
    Monday, April 17, 2017
    Rate of change (cont'd)
    Interpreting slope. Trends, minima & maxima.     		[slides-21]
    • Freedman 7.4-7.5 (available in D2L)
    Wednesday, April 19, 2017
    Linear regression
    Fitting and using lines.     		[slides-22]
    • Diez 7.1-7.2
    • Recommended: Freedman 12.1-12.3
    Friday, April 21, 2017
    Linear regression (cont'd)
    Residuals and mean squared error.     		[slides-23]
    • Diez 7.4
    Monday, April 24, 2017
    Linear regression (cont'd)
    Practicing regression in spreadsheets.
    Wednesday, April 26, 2017
    Derivatives
    Brief introduction to derivatives. Derivatives in Wolfram Alpha.     		[slides-24]
    Friday, April 28, 2017
    Derivatives (cont'd)
    Interpreting derivatives. Revisiting minima & maxima.     		[slides-24]
    Quiz 3 today
    Monday, May 1, 2017
    Derivatives (cont'd)
    Derivatives in practice.     		[slides-24]
    Wednesday, May 3, 2017
    Final Exam Review
    Review of semester.
    Friday, May 5, 2017
    Final Exam Review
    Review of semester.
    Final Exam Period
    Thursday, May 11, 2017
    Final Exam
    Time: 4:30pm–7:00pm       Location: HUMN 1B80 (our usual room)