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Schedule and Syllabus

Welcome to course website for MATH 256 - Intro to Probability and Statistics! On this page you can find all materials we’ll use throughout the semester, starting with the syllabus linked below:

You can find course content by scrolling, or by using the navigation bar in the upper left. Please note that some material may not be posted until we’ve reached that point in the course.

Homeworks

Homework is generally due every other Friday (with a few exceptions during weeks with exams).

In response to COVID-19, all submissions will done electronically via Canvas and are due at 11:59pm Eastern.

  • HW #1: 1.2, 1.9, 1.10, 1.25, 1.30, 1.40, 1.44, 2.10, 2.12, 2.13, 2.22
    • Due date: Friday 8/28
    • Please submit electronically through Canvas
  • HW #2: 3.1, 3.6, 3.10, 3.13, 3.14, 3.24, 3.29, 4.2, 4.7, 4.8, 4.17, 4.18, 4.19, 4.20
    • Due date: Friday 9/11
    • Please submit electronically through Canvas
  • HW #3: 5.4, 5.6, 5.7, 5.8, 5.12, 5.15, 5.21, 5.22, 6.1, 6.2, 6.11, 6.12, 6.19, 6.20 6.22
    • Due date: Friday 10/2
    • Please submit electronically through Canvas
    • Note: The due date for this assignment has been changed since the original posting. Additionally, questions 6.19, 6.20, 6.22 have been added to the assignment and question 5.29 has been moved to HW #4
  • HW #4: 5.20, 5.29, 5.30, 6.40, 6.42, 6.45, 6.46, 6.47, 6.48, 6.49
    • Due date: Friday 10/16
    • Please submit electronically through Canvas
    • Note: Our second exam is scheduled on the due-date of this assignment, I strongly encourage you to complete it before taking the exam
  • HW #5: 7.2, 7.7, 7.12, 7.17, 7.20, 7.24, 7.27, 7.28, 7.30
    • Due date: Friday 10/30
    • Please submit electronically through Canvas
  • HW #6: 7.37, 7.38, 7.47, 7.48, 7.52, 7.54, 8.6, 8.9, 8.31, 8.32, 8.37, 8.39
    • Due date: Friday 11/20
    • Please submit electronically through Canvas
    • Hints: For 7.54 recall we discussed multiple comparisons in this lecture

Announcements and Other Materials

  • Exam #1 is planned for Friday 9/18 at 9:00am
    • Everyone (ie: both groups) are expected to attend in-person, with half the class taking the exam in Alter 103 and the other half taking the exam in Alter 003
  • Exam #2 is planned for Friday 10/16 at 9:00am
    • This exam will be administered online via Canvas
  • Information on the class project can be found here
    • The first due-date is Monday 10/26 when you must submit your project proposal via Canvas
    • The second due-date is Monday 11/9 when you must have finalized and submitted your project dataset
    • Please consider using this template by pasting its contents into a blank .Rmd file
    • Information on how your project will be graded is available here
  • Exam #3 is tentatively planned for Friday 11/13 at 9:00am
  • The Final Exam date is Wednesday 12/2 (available all day)
    • The Final is open-notes and cumulative - you should review all past exams, lectures, and assignments to prepare

Datasets

  • Happy Planet
    • This dataset was assembled by The Happy Planet Index using data from a global survey that asks respondents questions about how they feel their lives are going. It documents the health and well-being of the inhabitants of various nations around the world.
  • Tips
    • These data were recorded by a waiter in national chain restaurant located in a suburban shopping mall in the early 1990s. The data document various aspects of each table served by the waiter, including the total bill, tip, size of the party, time of day, day of the week, and whether the party included a smoker. The data were originally obtained from the textbook: Interactive and Dynamic Graphics for Data Analysis: With R
  • Iowa City Home Sales
    • This dataset contains information on homes sold in Iowa City, IA between 2005 and 2008. It was scraped from the Johnson County county assessor website, and it contains information such as the home’s sale price, assessed value, square footage, and features.
  • Colleges 2019
    • This dataset contains select variables describing higher education institutions that primarily bachelors degrees. It was obtained from the College Scorecard, a comprehensive government database. For each institution, it includes enrollment and admissions variables, student demographics, costs and faculty salaries, as well as student outcomes such as median debt upon graduation and median 10-year salary.
  • Kobe’s 2009 Finals
    • This dataset documents every attempted shot from Kobe Byrant’s 2009 finals series against the Orlando Magic. The Lakers won the series in 5 games, and Kobe was named the finals MVP for his performance.
  • TSA Claims
    • The Transport Security Administration (TSA) is an agency within the US Department of Homeland Security that has authority of the safety and security of travel in the United States. This dataset documents claims made by travelers against the TSA in 2004 and 2005, including information of the claim type, claim amount, and whether it was approved, settled, or denied.
  • Police-involved Killings
    • The Washington Post manages a comprehensive database of instances where police officers have used deadly force on an suspect dating back to 2015. This dataset documents these cases, including variables such as the age, race, and gender of the individual who was killed, as well as variables describing the circumstances of the incident, such as whether the individual killed was armed, whether police officers had body cameras, etc.
  • Wetsuits
    • This dataset contains 1500m swim velocities for 12 competitive swimmers when wearing a specially designed wetsuit and without the wetsuit. These data were obtained from the Lock5stat data page.
  • Mass Shootings
    • This dataset was originally assembled in response to the movie theater shooting in Aurora Colorado by Mother Jones, a liberal news organization. It documents shootings in the United States where a lone gunman (with a few exceptions involving two shooters) killed at least four individuals (not including themselves) at a single location (with a few exceptions involving multiple locations within a short period). Variables include: demographic characteristics of the shooter, information on when/where the shooting occurred, information on the number of victims, and information about the mental health status of the shooter.
  • Tailgating and Drug Use
    • Participants were recruited based upon their self-reported drug use and asked to follow an erratically behaving lead vehicle as part of a driving simulator experiment under the working hypothesis that regular users of certain drugs would exhibit more risky driving behavior. The data were derived from a study conducted by the National Advanced Driving Simulator organization.