Mathematics 363

Introduction to Statistical Methods

Fall 2014

Course Home Page

 

 

Course Syllabus 

Resource Webpage

 

Overview.

In Introduction to Statistical Methods, we shall be using your background in biology, economics, or engineering and your previous knowledge of algebra, calculus and differential equations to consider the issues of collection, model derivation and analysis, interpretation, explanation, and presentation of data.  The objective this course is to take advantage of the coherent body of knowledge provided by statistical theory having an eye consistently on the application of the subject. This approach will allow you to extend your ability to use statistical methods beyond those given in the course.

 

The major prerequisites are comfort with calculus and a strong interest in questions that can benefit from statistical analysis.  Willingness to engage in explorations utilizing statistical software is an important additional requirement. Even though many of our examples are derive from the life sciences, statistics is applicable to a wide variety of academic disciplines, from the natural and social sciences to the humanities.

 

Day-to-Day Operations. 

The class meets Tuesdays and Thursdays from 9:30 AM to 10:45 AM in room 333 of Education Building. The schedule of topics, the course textbook, and assignments are given in the course syllabus. 

 

This semester, we will be flipping the class – thus, you will be typically listening to 5 to 6 short lectures, answering 2 to 3 check point exercises and submitting them before the beginning of class. The class will begin with a discussion meant to assess your understanding of the lectures and to discuss the assignment. Most of the class will be devoted to using a worksheet having one or two statistics or probability problems. Much of the work can be completed during class time. Typically, you will work in pairs, so you will need to bring a laptop to class.

 

The class will have an graduate teaching assistant, Julia Fisher. Julia is simultaneously pursuing a doctoral degree in linguistics and a masters degree in statistics.

 

name

email

office hours

location

Joe Watkins

jwatkins at math.arizona.edu

11:00-12:00 Monday

12:00-12:30 Monday

1:00-2:30 Wednesday

220 Mathematics

522 Mathematics

522 Mathematics

Julia Fisher

jmfisher at email.arizona.edu

11:00-12:30 Tuesday

11:00-12:30 Thursday

220 Mathematics

220 Mathematics

 

Feel free to stop by my office in the Mathematics Building, call me at 621-5245 or send an email.

 

Use of Software.

We will do some software computation using R.  R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. To download R, please choose your preferred CRAN mirror. As with any computer software, the syntax in R will seem awkward at first. Many of you will also want to download Rstudio, which is also free.

 

Copies of Introductory Statistics with R by Peter Dalgaard are available at the bookstore. Other options for software assistance can be found on the resource webpage.

 

Evaluation of Students.

We shall have 2 in-class midterm exams and a comprehensive final exam. Our final is scheduled for Wednesday, December 17th, 2014 from 10:30 am to 12:30 pm.

 

Permission to turn in late homework for credit must be arranged in advance. Students will also design and complete a project that analyzes data using statistical software.

 

The grading scheme is

 

number

points

total

check points

worksheets

22

20

5

10

110

200

midterm exams

2

100

200

project

1

50

50

final exam

1

175

175

total

735

 

The check points are short exercises described in the videos and are meant to solidify your understanding of a concept. These are due in the D2L dropbox midnight the evening before class. The worksheets are generally 1 or 2 problems with several parts that are designed to deepen and integrate your knowledge. We will start on the worksheet problems in class. You will often need to complete the worksheet after class. These are due at the beginning of the following class. Students are encouraged to work together, but everyone is expected to turn in their own assignment either to the dropbox or in class. We will keep the top 22 check point scores and 20 worksheet scores. In addition, we will have ~4 optional sections on more advanced topics (indicated in red). Check point exercises for these sections will be counted as extra credit.

 

Grades will be given on the usual scale A is 90%-100%, B is 80%-89%, C is 70%-79%, D is 60%-69%, and E is below 60%. The instructors may move these cutoff values down. If you fail to complete the course due to circumstances unforeseen, then you may qualify for a grade of I, "incomplete" if all of the conditions are met:

 

 

Students should take the time to become familiar with policies and codes of the University. Student with special needs should contact SALT - Strategic Alternative Learning Techniques Center or the Disability Resources Center.

 

Best wishes to you for a good semester in this course and in all your other activities.

 

  - Joe Watkins