Syllabus
STA2023 – Introduction to Statistics I
Fall 2018
1
I
NSTRUCTIONAL
T
EAM
Course Coordinator
Lab Coordinator
Teaching Assistants
Maria Ripol
Stephanie Stine
~16 TAs
- names and emails
Email
[email protected]
[email protected]
available in Canvas
Office
Griffin Floyd 117C
Griffin Floyd 117B
Griffin Floyd 104 Tutoring
Room
Phone
352-273-2976
352-273-2975
office
hours
MWF 4
th
and 5
th
periods
or by appointment
MTR 10:30am – 12 noon
or by appointment
In Tutoring Room (see Canvas
for schedule)
contact
for:
Questions about quiz and
exam grades.
General questions about the
course not answered on the
syllabus or the homepage in
Canvas.
Questions about lab.
Incorrectly recorded grades
on lab worksheet.
Course material – In Tutoring
Room (see Canvas for
schedule)
Website
Course website in Canvas at
2
M
ATERIALS
Lecture Notes
– these are available two different ways. You can print them (for free) from the course
homepage in Canvas, or you can purchase them in the
Lab Workbook for Statistics: The Art and Science
of Learning from Data
by Megan Mocko and Maria Ripol, 4th edition, 2017, Pearson ISBN:
9780133860894.
Lab Worksheets
– needed for the lab portion of the course, and available to print from the course
homepage in Canvas.
Scientific Calculator
- You will need a calculator with some basic statistical functions: mean and standard
deviation. Many inexpensive calculators (around $15) have these functions; check the manual or look
for the following symbols: x-
bar and either s or σn
-1. Graphing calculators are NOT ALLOWED on exams.
Textbook:
Statistics:
The Art and Science of Learning from Data
by Agresti, Franklin, Klingenberg, 4th
edition, Pearson, 2017.
Textbook can be purchased three ways: hardbound new or used ISBN13:
9780321997838; bundled with the Lab Workbook ISBN: 9780134567662; as an ebook from the
publisher - see Canvas for details.

3
C
OURSE
D
ESCRIPTION
STA 2023 is an introductory course that assumes no prior knowledge of statistics but does assume some
knowledge of high school algebra. Basic statistical concepts and methods are presented in a manner
that emphasizes understanding the principles of data collection and analysis rather than theory.
Much
of the course will be devoted to discussions of how statistics is commonly used in the real world.
There
are two major parts to this course:
I
Data – which includes graphical and numerical summaries to describe the distribution of a
variable, or the relationship between two variables (chapters 1, 2 and 3, approximately 3 weeks),
and data production to learn how to design good surveys and experiments, collect data from
samples that are representative of the whole population, and avoid common sources of biases
(chapter 4, 1 week.)
II
Probability and Inference – using the language of probability and the properties of numerical
summaries computed from a random samples (chapters 5, 6 and 7, 4 weeks), we learn to draw
conclusions about the population of interest, based on our random sample, and attach a measure of
reliability to them (chapters 8, 9, 10
approximately 8 weeks).