Standard statistical reasoning. Simple statistical methods. Social/physical sciences. Mathematical reasoning behind facts in daily news. Basic computing environment.

Instructor

Logistics

Content

What is this course about?

This is an introductory statistics course intended for undergraduate students. Topics include exploratory data analysis (graphs and simple summary statistics), inference using hypothesis tests and confidence intervals, simple linear regression, one-way ANOVA, and chi-squared tests for two- way tables. Emphasis will be placed on being able to use these tools with real data. Students are expected to be comfortable with computers as we will be using R on a regular basis.

“All models are wrong, but some are useful.” – George E. P. Box

Reference Texts

The following texts are useful, but none are required.

Helpful Resources

The following resources are helpful, but none are required.


Coursework

Assignments (20%)

There are nine weekly assignments, which will improve both your theoretical understanding and your practical skills. All assignments contain both written questions and programming parts. All assignments must be turned into Canvas no later than 11:59 pm (U.S. Central Time) on due dates. Late submissions will not be accepted. All deadlines are listed in the schedule.

Participation (0%)

We appreciate everyone being actively involved in the class! At the same time, participation is not counted in credits.

Mid-term Exams (50%)

We will have two mid-term exams. Exam 1 is on October 20, 5:00 pm - 6:30 pm, at Anderson 310. Exam 2 is on November 17, 5:00 pm - 6:30 pm, at Anderson 310.

Final Exam (30%)

The final exam is cumulative. It will be on December 20, 5:00 pm - 7:00 pm, location TBD.


Schedule

Updated lecture slides will be posted here shortly before each lecture.

Date Description Course Materials Events Deadlines
Tue Sep 6 R and RStudio Installation Suggested Readings:
  1. Introduction to R
Wed Sep 7 Course Overview
[slides]

Introduction to R and RStudio
Suggested Readings:
  1. Syllabus
  2. Handout Table of Contents
  3. Handout Chapter 1
  4. R Reference Guide
  5. RStudio Cloud Guide
Fri Sep 9 Chapter 1: Introduction
[slides]

Chapter 2: Exploring Data
[slides] [code] [data]
Suggested Readings:
  1. Handout Chapter 1
  2. Textbook p1 - p24
  3. Handout Chapter 2.1, 2.2.1, 2.3
HW 0 out

Make-up Exam Sign-up available
HW 0 due
Mon Sep 12 Chapter 2: Exploring Data
[slides] [code] [data]
Suggested Readings:
  1. Handout Chapter 2.3
Tue Sep 13 Lab 0: Data Importing and Data Summaries Suggested Readings:
  1. Lab 0 Handout
Wed Sep 14 Chapter 2: Exploring Data
[slides] [code] [data]
Suggested Readings:
  1. Handout Chapter 2.2, 2.3
Old Exams out

Office Hour Vote out
Fri Sep 16
[Zoom]
Chapter 4: Gathering Data
[slides]
Suggested Readings:
  1. Handout Chapter 4
  2. Textbook p153-172
HW 1 out Office Hour Vote due
Mon Sep 19
[Zoom Recordings]
Chapter 5: Probability
[slides] [code]
Suggested Readings:
  1. Handout Chapter 5
  2. Textbook p200-232
Tue Sep 20 Lab 1 Suggested Readings:
  1. Lab 1 Handout
Wed Sep 21
[Zoom Recording]
Chapter 5: Probability
[slides]
Suggested Readings:
  1. Handout Chapter 5
  2. Textbook p200-232
Fri Sep 23
[Zoom]
Review Chapter 5

Chapter 6: Probability Distribution
[slides]
Suggested Readings:
  1. Handout Chapter 6.1, 6.3
  2. Textbook p254-266, p279-289
  3. Chapter 5, 6 Mindmap
HW 2 out HW 1 due on Sunday
Mon Sep 26
[Zoom]
Chapter 6: Probability Distribution
[slides] [code]
Suggested Readings:
  1. Handout Chapter 6.3
  2. Textbook p279-289
HW 1 Solution out
Tue Sep 27 Lab 2 Suggested Readings:
  1. Lab 2 Handout
Wed Sep 28 Chapter 6: Probability Distribution
[slides] [code]
Suggested Readings:
  1. Handout Chapter 6.2
  2. Textbook p267-279
Spring23 TA Hiring out
Fri Sep 30 Chapter 6: Probability Distribution
[slides] [code]
Suggested Readings:
  1. Handout Chapter 6.2
  2. Textbook p267-279
HW 3 out HW 2 due on Sunday
Mon Oct 3 Chapter 6: Probability Distribution
[slides] [code]

Chapter 7: Sampling Distributions
[slides] [code]
Suggested Readings:
  1. Handout Chapter 7
  2. Textbook p298-323
HW 2 Solution out

Example 6.8 Correction out

HW 1 Grade out
Tue Oct 4 Lab 3 Suggested Readings:
  1. Lab 3 Handout
Wed Oct 5 Chapter 7: Sampling Distributions
[slides] [code]
Suggested Readings:
  1. Handout Chapter 7
  2. Textbook p298-323