PY211 – Elementary Statistical Methods
Tuesday/Thursday 2:00pm – 3:15pm, room: GP 206
Instructor: Dr. André L Souza
Office hours: by appointment only at www.doodle.com/andresouza
Class Webpage: http://asouza.people.ua.edu/teaching
Required Text: Nolan, S.A., & Heinzen, T.E. (2011). Essentials of Statistics for the Behavioral Sciences.
Worth Publishers: New York
Course description: This is an undergraduate level statistics course. It is an introduction to
statistical methods employed to analyze data in experimental psychology. It will focus on the main
concepts behind key statistical methods and their applications to real data. Topics dealt with in class
include entering and arranging data in spreadsheets, frequency distributions, measures of central
tendency and variability, the Normal Distribution, principles of probability theory, hypothesis testing,
t-test, linear regression and Analysis of Variance. At the end of the course you should be able to
know/understand/identify:
• what statistics is and how we can use it to make informed decisions in psychology
• the fundamentals of statistical modeling
• how to quantify and interpret variability in data
• how to meaningfully plot your data
• when and how to use a t-test, regression and ANOVA
This is not a math course; however basic understanding of elementary math is required. PY211 is
probably one of the most intellectually demanding, important and time-consuming courses you will
take. You will be performing lots of computations by hand and on the computer. For the computerbased computations we will use the software SPSS and the computational language R. SPSS is
available in many computer labs across campus. R is available free of charge at http://www.rproject.org/.
Letter grade conversion:
A+
97-100
A
93-96
A90-92
B+
87-89
B
83-86
B80-82
C+
77-79
C
73-76
C70-72
D+
67-69
D
63-66
D60-62
F
≤ 59
Grading breakdown:
•
•
Three exams: 90% (5% for the lowest score and 42.5% for the other two)
Data analysis project: 10%
A few very important remarks
I treat every student in the class equally, fairly, and as a responsible, mature adult whose goal is to
commit and learn the material covered in class. I understand that people have bad testing days, or
that an emergency may result in poor exam performance. However, when you registered for this
course, you made a commitment to it. In the light of this commitment, I expect you to attend the
class, arrive on time, be attentive, and behave in an honest, responsible, and mature manner.
This is a very difficult class. The course will move in a fast pace. Do not wait until the last minute
and “cram” information for the exams. Keep up with the material and ask questions when you are
unclear about something. The topics covered in this class will form the basis of your statistical
knowledge for the rest of your career. Make sure you construct a very solid foundation.
Arrive on time: It is your responsibility to arrive on time for each class. I am very picky about this.
Arriving late is disruptive for the class and for the instructor.
Attendance: You are expected to attend every class.
Read the assigned material prior to coming to class: Reading the material before class is
mandatory and helps you find the material more interesting, informative and easier to understand.
Again, all assigned readings are mandatory.
Exams: Exams are cumulative. This makes perfect sense in the context of Statistics, that is, concepts
learned on day 1 will be recurrent in all exams.
No make up exams: No excuses! Make sure you attend each exam. There will be no exceptions to
this rule.
Cellphones, iPads and laptops: mobile phones are to be off and left to themselves during lecture. If
you interact with your mobile phone during class, you will be asked to leave. Laptops and iPads are
to be used for taking-notes purpose only. Facebooking, Youtubing, and any other sort of Internet
activity (including checking your e-mail) will not be permitted. Only come to class if you plan to be
100% focused.
Code of Academic Conduct Statement: All acts of dishonesty in any work constitute academic
misconduct and will not be tolerated. This includes, but is not limited to, cheating, plagiarism,
fabrication of information, misrepresentations, and abetting any of the above. The Academic
Misconduct Disciplinary Policy will be followed in the event that academic misconduct occurs.
Please refer to the Student Affairs Handbook, which can be obtained in the Office of Student Life
and Services in the Ferguson Center, for more information. Additionally, students are expected to
uphold the University’s Code of Academic Conduct Statement, which reads: All students in attendance
at the University of Alabama are expected to be honorable and to observe standards of conduct appropriate to a
community of scholars. The University expects from its students a higher standard of conduct than the minimum
required to avoid discipline. Academic misconduct includes all acts of dishonesty in any academically related matter and
any knowing or intentional help or attempt to help, or conspiracy to help, another student.
Special Needs: If you require assistance in the classroom due to a disability of any type, please
contact Disability Services at (205) 348-4285 during the first week of the semester so that appropriate
accommodations can be made. After initial arrangements have been made with Disability Services,
contact us immediately.
In case of an emergency: The primary University communication tool for sending out information
is the web site www.ua.edu. Students should consult this site as soon as they can in an emergency.
The course syllabus is posted at www.asouza.people.ua.edu/teaching, and in case of an emergency,
we will give information on the course through Blackboard.
Tentative Schedule
Lecture
Lecture 1
Lecture 2
Lecture 3
Lecture 4
Lecture 5
Lecture 6
Lecture 7
Lecture 8
Lecture 9
Lecture 10
Lecture 11
Lecture 12
Lecture 13
Lecture 14
Lecture 15
Lecture 16
Lecture 17
Lecture 18
Lecture 19
Lecture 20
Lecture 21
Lecture 22
Lecture 23
Lecture 24
Lecture 25
Lecture 26
Lecture 27
Lecture 28
Lecture 29
Lecture 30
Lecture 31
Date
21-Aug
26-Aug
28-Aug
02-Sep
04-Sep
09-Sep
11-Sep
16-Sep
18-Sep
23-Sep
25-Sep
30-Sep
02-Oct
07-Oct
09-Oct
14-Oct
16-Oct
21-Oct
23-Oct
28-Oct
30-Oct
04-Nov
06-Nov
11-Nov
13-Nov
18-Nov
20-Nov
25-Nov
27-Nov
02-Dec
04-Dec
Content/Topic Covered
Course Intro
Introduction to Statistical Modeling
Frequency distribution
Graphing your data
Class Canceled
Central Tendency and Variability
Central Tendency and Variability
Principles of Probability
Exam 1 review session
Exam 1
The Normal Distribution
Class Canceled
Intro to Hypothesis testing
Hypothesis testing (four steps)
Hypothesis testing (z-scores)
Confidence intervals
One sample t-test
Paired samples + Independent Samples t-test
Independent samples t-test + Effect Sizes
Exam 2
Mid-semester study break
Exam 2 review
Statistical Power
One-way Analysis of Variance
Two-way Analysis of Variance
Correlation
Linear regression
Linear regression
Thanksgiving
Chi square analysis
Final Exam review session
Reference chapter
Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 4
Chapter 5
Chapter 6
Chapter 7
Chapter 7
Chapter 7
Chapter 8
Chapter 9
Chapters 8 and 9
Chapter 10
Chapter 8
Chapter 11
Chapter 12
Chapter 13
Chapter 14
Chapter 14
Chapter 15
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