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Introduction to Statistical Methods (STAT 301)
Syllabus
Fall 2014
IMPORTANT NOTE!! This syllabus is tentative and subject to change. I will give ample notice of changes in class and online.
Instructor: Josh Hewitt, [email protected] Office hours: Tilt Great Hall, Tuesday 2-4 p.m., or by appointment.
Grader: Lyuou Zhang, [email protected]
Lecture: Section 1. Clark A 204, MWF 8-8:50 a.m.
Course webpages: Schedules, projects, additional notes, copies of announcements, and other course materials and information will be available on RamCT and updated regularly. Homework assignments will be available on WebAssign.
Study sessions: In addition to office hours, TILT offers weekly, open, student-led study group sessions for Stat 301. Meeting times are currently TBD and will be announced in class.
Prerequisites: Any of MATH 117, 118, 124, 125, 126, 141, 155, or 160, or permission of instructor.
Course description: Techniques in statistical inference; confidence intervals, hypothesis tests, correlation and regression, analysis of variance, chi-square tests.
Course goals: This course should give you a working knowledge of classic statistical methods. Statistics provides a set of tools that quantify the strength and reliability of patterns. This course introduces you to classic tools that help answer questions which permeate science and culture, for example “is there a real difference between these two options”, and “how much does one thing impact another?”. To gain an appreciation for their practical use, you will also have opportunities to apply these tools to illustrative datasets. Lastly, this course also introduces you to limitations of classic methods—you will see how to apply these tools and not be misled by them.
Required tools: You need a TI-83/4 (or other equivalent) calculator, as well as StatCrunch (statcrunch.com) and WebAssign accounts (webassign.com, class key: colostate 0156 5878).
Optional texts: OpenIntro Statistics (2nd^ ed.) This is a free open source text that is available for download at http://www.openintro.org/stat/textbook.php. Paper copies are also available on amazon.com.
The Cartoon Guide to Statistics by Larry Gonick. This is a lighthearted introduction to concepts and symbols used in statistics. It has great historical factoids and nicely highlights important things to remember.
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Grades: Your overall course grade will be a weighted average of the semester’s homework, projects, exams, and projects:
Homework 30% Projects 30% Midterm 1 10% Midterm 2 10% Final 20%
Note: Within each category, all assignments are weighted equally. For example, a homework that “is worth” 30 points counts as much toward your final grade as a homework that “is worth” 55 points.
Grading issues: Don’t wait. Within a week, try to contact me as soon as possible about grading errors you find or questions you have.
Homework/Projects: WebAssign homework is assigned weekly and projects are assigned periodically. You are generally encouraged to work with your classmates on out of class assignments, but all submissions must reflect your own work.
Exam dates: Exam 1 - 10/3, Exam 2 - 11/7, Final - 12/17 9:40-11:40a. All exams are in-class. RDS students should contact me to make alternate arrangements.
Study expectations: Statistics uses concepts you may not have studied in depth before. That’s why we have this class! There is no right or wrong amount of time you need to study, but you should not feel discouraged if you feel successful in achieving your goals after spending between 3 and 9 hours each week working or studying outside of class. This advice applies to everyone.
Late/Make-up policy: Generally, late work is not accepted and missed exams cannot be made up. However, reasonable exceptions are allowable. Certain school-sponsored activities with proper documentation, like sports travel and games, are clear exceptions. Contact me as soon as possible if you anticipate or know you will need to have assignments extended or exams rescheduled.
Academic integrity: I think that NYU Steinhardt says it best that “Your degree should represent genuine learning.” It is important that you do not use another person’s work as your own and that you do not seek outside help or resources when you are not allowed to do so. These actions violate CSU’s Academic Integrity Policy. It is more important for your future success, growth, confidence, and abilities to have to work hard and struggle than it is to pretend otherwise. Please ask me about situations you think may violate CSU’s Academic Integrity Policy.
This course will adhere to the CSU Academic Integrity Policy as found in the General Catalog and the Student Conduct Code. At a minimum, violations will result in a grading penalty in this course and a report to the Office of Conflict Resolution and Student Conduct Services.
