Statistics
and Data Science 363
Introduction
to Statistical Methods
Fall 2018
Course
Home Page
Overview.
Introduction to Statistical Methods (DATA363) is the foundation course for the Statistics and Data Science
undergraduate major and minor. We shall be using your background in the natural
or social sciences, the humanities, or engineering and your previous knowledge
of algebra, calculus and linear algebra 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 methods in
data science 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. 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 and engineering.
Day-to-Day Operations.
The class meets Tuesdays and Thursdays from
2:00 to 3:15 PM in room 208 of Biological
Sciences West. 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 |
9:00-10:00 Mondays 11:30- 12:30 Tuesdays 1:30- 2:30 Thursdays |
S321 ENR2 522 Mathematics 522 Mathematics |
Feel free to stop by my offices in the Mathematics Building
or in the Environmental
and Natural Resources Building 2 (ENR2), 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 Assignments 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 in-class midterm exams and a comprehensive
final exam. Our
final is scheduled for
Wednesday, December 12th, 2018 from 1:00 pm to 3:00 pm.
Students who are unable to attend an exam should notify the
instructor as soon as possible. Arrangements for a make-up test will be
considered on a case-by-case basis. Make-up 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, Ҽa
href="http://www.registrar.arizona.edu/gradepolicy/incomplete.htm">incompleteӍ 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