Mathematics 363
Introduction to
Statistical Methods
Fall 2017
Course Home Page
Overview.
In Introduction
to Statistical Methods, we shall be using your background in the natural or
social sciences, the humanities, 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 derived from the life
sciences, the breadth of our examples will show that statistics is applicable to
a wide variety of academic disciplines, from the natural and social sciences to
the humanities.
DaytoDay Operations.
The class meets Tuesdays and Thursdays from 9:30 AM to 10:45 AM
in room 301 of Cesar
Chavez Building. The schedule of topics, the course textbook, and
assignments are given in the course syllabus.
This course is taught using a flipped format. Thus, you will be
typically listening to 5 to 6 short lectures, answering 2 to 3 checkpoint exercises and submitting responses the night before class.
The class will begin with a discussion 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. The worksheets are due in at the
beginning of the subsequent class. Typically, you will work in pairs. Students are expected to attend class and
contribute to the classroom activities. So, you will need to bring a laptop to class.
instructor 
email 
office hours 
location 
Joe Watkins 
jwatkins at
math.arizona.edu 
Monday
11:0012:00 Wednesday
1:002:00 Wednesday
2:003:00 
220
Mathematics 522
Mathematics 522
Mathematics 
Ning Hao 
nhao
at math.arizona.edu 
Mondays
2:003:00 Thursday
11:0012:00 Thursday
12:001:00 
325 ENR2 325 ENR2 220 Mathematics 
Alixx
Encinas 
acencina
at email.arizona.edu 
Tuesday
11:001:00 
513 Mathematics 
Feel free to stop by our offices in the Mathematics Building
or in the Environmental
and Natural Resources Building 2, room S321 and S324 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. Rstudio
provides a graphical user interface that will make the use of R go more
smoothly.
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.
_
The checkpoints 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.
Check point exercises are graded
based on honest effort.
_
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, and consequently students are expected to attend class. Everyone is expected to turn
in their own assignment. Worksheets
will be marked according to the following guidelines. 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.
_
We shall have 2 inclass midterm exams and a
comprehensive final
exam. Our final is scheduled for
Tuesday,
December 12th, 2017 from 8:00 am to 10:00 am.
Students
who are unable to attend an exam should notify the instructor as soon as
possible.
Arrangements for a makeup test will be considered on a casebycase
basis. Makeup exams will be administered only at the discretion of the
instructor at a mutually arranged time.
Failure to contact the instructor will result in a grade of zero on the
exam.
We will keep the top 22 checkpoint scores and 20 worksheet
scores. In addition, we will have ~5 optional sections on more advanced topics
(indicated in red). Check point exercises for
these sections will be counted as extra credit.
The grading scheme is
number 
points 
total 

check points worksheets 
22 20 
5 10 
110 200 
midterm exams 
2 
100 
200 
project 
1 
65 
65 
final exam 
1 
175 
175 
total 
750 
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 instructor may move these cutoff values down. Any
grading disputes must be addressed within one week after an exam or homework
has been returned. If you fail to complete the course due to circumstances
unforeseen, then you may qualify for a grade of I, ÒincompleteÓ
in accordance with University Policy.
Honors Contracts.
This course is
available for honors contract.
Students who elect sign an honors contract will be given a project to
complete in lieu of some of the written homework assignments, and the project
grade will replace the corresponding homework grades. To negotiate the details of an honors
contract for this course, please contact the instructor within the first week
of classes.
Students should take the time to become familiar with policies and codes
of the University, notably the academic
integrity policy and student
code of conduct. 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