Graham, Jonathan Mills

English

University of Montana

University of MontanaScholarWorks at University of MontanaSyllabi Course SyllabiFall 9-1-2018STAT 451.00: Statistical Methods IJonathan Mills GrahamUniversity of Montana, MissoulaLet us know how access to this document benefits you.Follow this and additional works at: https://scholarworks.umt.edu/syllabiThis Syllabus is brought to you for free and open access by the Course Syllabi at ScholarWorks at University of Montana. It has been accepted forinclusion in Syllabi by an authorized administrator of ScholarWorks at University of Montana. For more information, please contactscholarworks@mso.umt.edu.Recommended CitationGraham, Jonathan Mills, "STAT 451.00: Statistical Methods I" (2018). Syllabi. 8202.https://scholarworks.umt.edu/syllabi/8202                                                                                                                                                                                                                                                                                                                                                                        Syllabus�STAT 451, Statistical Methods I�Fall 2018, MWF 9:00-9:50am (Section 1), 10:00-10:50am (Section 2) in Math 108�Course Information:•	 Instructor: Jon Graham, Math 204, 243-2561, jgraham@mso.umt.edu.•	 Textbook: Statistical Methods & Data Analysis, 7th ed., by Ott & Longnecker•	 Office Hours: To be announced, By appointment•	 Course Webpage: Accessed through Moodle•	 Grading: Homework: 30% Exams 1,2: 40% Final: 30%•	 Prerequisites: One year of college mathematics including M115. A previous course inprobability is useful (not required), and no background in statistics is assumed.Homework Homework will typically be assigned every Friday, to be handed in at the beginning ofclass the following Friday. NO LATE HOMEWORK WILL BE ACCEPTED FOR ANY REASON,and the lowest homework grade will be dropped. Homework is not only a fairlysubstantial portion of your grade, but is vital to your success in this class. Working withother students on homework is encouraged, as long as you hand in your own work, anddo not simply copy someone else's work. Solutions to all problems will be provided.Exams Exams 1 & 2 will be cumulative and closed book. More about the exams, including theexact dates of the exams will be given later. If you cannot make it to an exam, you mustlet me know BEFORE the exam is given. No make-up exams will be given without adocumentable reason for missing the exam.Final Exam The Final exam is scheduled for 8:00-10:00am on Wednesday, December 12 for Section1 and 8:00am-10:00am on Thursday, December 13 for Section 2.Course Material and Objectives This course is an introduction to statistical methods for analyzing data. The course isintended primarily for students in disciplines outside of mathematics who are seekingstatistical tools for data analysis. After some sampling and design issues and anintroduction to exploratory analysis, the course will focus on probability distributions,relationships between variables, statistical inference through estimation, hypothesistesting, and confidence intervals, categorical data, and linear regression. Both in classand on homeworks, the software package R will be used to illustrate statisticaltechniques and elucidate statistical concepts.                                                                                                                                                                                                                                                                                                                                                                                  Questions are strongly encouraged, both during class and at office hours. If you are lost andconfused, please let me know.Important Dates Monday, September 3: Labor Day holiday�Monday, September 17: Last day to add courses by Cyberbear.Monday, September 17: Last day to drop courses/change grading option in Cyberbear.Monday, October 29: Last day to drop courses. Paper form must be signed by advisorand instructor. A W will appear on your transcript. After this date, drops can only bedone by with the Dean’s signature.Tuesday, November 6: Election DayMonday, November 12: Veterans DayWednesday, November 21 – Friday, November 23: Thanksgiving holidayFriday, December 7: Last day to change grading option (letter grade to CR/NCR orvice-versa). Requires paper form signed by advisor and instructor.Learning Outcomes: Upon successful completion of STAT 341, a student will:1.	 Learn how to describe and explore sets of data both numerically and graphically.2.	 Learn about the normal, binomial, and other basic models for the distribution of a singlevariable and the linear regression model for the relationship between two variables.3.	 Learn the basic ideas of good experimental design and good sampling design.4.	 Understand some basic probability theory, and the importance of the normaldistribution and Central Limit Theorem to statistical inference.5.	 Learn the fundamental ideas of statistical inference for means and proportions includingboth hypothesis testing and confidence intervals.6.	 Learn how to critically evaluate scientific journal articles with respect to the materiallearned in this class.Disability Services The University of Montana assures equal access to instruction through collaboration be­tween students with disabilities, instructors, and Disability Services for Students (DSS). Ifyou think you may have a disability adversely affecting your academic performance, andyou have not already registered with DSS, please contact DSS in Lommasson 154. I willwork with you and DSS to provide an appropriate accommodation.Academic Honesty All students must practice academic honesty. Academic misconduct is subject to anacademic penalty by the course instructor and/or a disciplinary action by the University.All students need to be familiar with the Student Conduct Code. You can find it in theA-Z index on the UM home page.

STAT 451.00: Statistical Methods I

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STAT 451.00: Statistical Methods I

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