UC Berkeley
Fall 2014
PSYCH 101/10 Research and Data Analysis in
Psychology
Course Objectives: In this course you should gain the ability to understand and explain the
statistical analyses in reports of psychological research. You should learn to identify and compute
the appropriate statistical procedures for many basic research scenarios and interpret results. This
course is also designed to improve your quantitative and analytic thinking skills, as well as your
appreciation of psychology as a science. The lecture for this class is held 2 times per week, in
addition to 1 computer lab/discussion section per week. Lectures will contain information not
available in your textbook and will emphasize the intuitive understanding of statistical reasoning.
Lab sections will include a review of the course material and homework assignments, with a
focus on statistical computation and data analysis.
Text and materials: Statistics for Psychology (Pearson; 6th Ed.) by Aron, Aron, & Coups (2013)
ISBN-10: 0205258158, ISBN-13: 9780205258154. Two copies of the textbook are available on
reserve (2 hr) at the Ed/Psych Library.
Web chapters are available at: http://www.pearsonhighered.com/aron.
A laptop computer is required for this course.
You will need to download R, a free computer software environment for statistical computing
and graphics, at http://cran.cnr.berkeley.edu/.
Graduate Student Instructors
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Lab Section Schedule
Section
101
102
103
104
105
106
107
108
109
110
Weekday
Monday
Monday
Tuesday
Tuesday
Wednesday
Wednesday
Wednesday
Thursday
Friday
Friday
Time
10 - 12 PM
12 - 2 PM
12 - 2 PM
2 - 4 PM
9 - 11 PM
11 – 1 PM
1 – 3 PM
1 – 3 PM
10 – 12 PM
12 – 2 PM
Computer lab sections meet in 1535 TOLMAN (Tolman Microcomputer Facility)
Attendance at and active participation in laboratory sections are required for 15% of your grade.
In each lab section you will be required to complete an activity and submit it or show it to your
GSI for participation credit.
Drop-in time is available anytime the lab is open but a class is not scheduled. You can use these drop-in times to
finish your homework (as needed) and to work on the data analysis for your final project. The room is open M-Th
9a-6p and F 9a-5p. For the Tolman lab, each half of the room is scheduled separately, so there are many drop-in
hours. They are posted weekly at (TMFa and TMFb): http://facility.berkeley.edu/labs/hourstmf.html. There is no
food or drink allowed, though closed water bottles may be placed on the floor.
Exams: There will be four exams, each worth 90 points (15% of your grade). Exams will cover
material in the assigned readings, the lectures and the lab. The exams will be cumulative, but will
be weighted toward the most recent material. You will be allowed to bring one page of notes
(double sided, 8.5 x 11 inch paper, hand-written) and a calculator to each exam. You are expected
to abide by all the rules and regulations governing student conduct and ethical academic behavior
issued by the Student Conduct Office http://sa.berkeley.edu/code-of-conduct. Because of the
homework assignment replacement option (see below), no late, early or make-up exams will be
offered. Should an emergency, extra curricular activity, family event, or similar prevent you
from taking a scheduled exam at the scheduled time, you may replace the exam score with your
homework score.
Homework: There will be 10 homework assignments designed to help you learn. Assignments
will be worth 9 points each (adding up to 90 points total: 15% of your grade). Due dates are
provided on the bottom of this syllabus. Each assignment will be announced in lecture and
posted online. You have the option of completing homework or avoiding it all together. If you
choose to complete homework, your assignments point total can be used to replace your lowest
exam score. If the homework adds up to less than the total points earned on your lowest exam,
your homework score will be omitted from your final grade calculation. Because of this option,
late work will not be accepted under any circumstances. If you will miss a class (due to
emergency, extra curricular activity, family event, or similar), find a way to submit the
assignment before the due date or through another channel. Assignments are to be submitted on
the due date in lecture at the start of class.
Course Project: Instead of taking a final exam in this class, you will be completing a final
project. The final project will require you to demonstrate an understanding of research design,
methodology, and data analysis in by conducting your own research. This project is worth 120
points (20% of your grade). See the course project description document for details.
RPP: Our class will participate in the Research Participation Program. For 3 hours of research
participation, you will receive 3 RPP credits. This required participation counts for 5% of the
grade. To learn how to create an RPP account and start participating in experiments, visit http://
psychology.berkeley.edu/rpp/ and click on "Important Information for Students." If you have any
questions, contact RPP at rpp@berkeley.edu.
Grades: Grades are based on performance in the labs, your final project, RPP, and exams.
Computer Lab
RPP
Exams
(Homework)
Final Project
% of grade
15%
5%
60% (4 at 15% each)
(15%)
20%
points possible
90
30
360
(90)
120
total=600
Your course grade will be based on
an absolute scale:
Letter Grade
A+
A
AB+
B
BC+
C
CD
F
Minimum Percent
98
93
90
88
83
80
78
73
70
60
0
NOTE: We cannot accept extra credit or make any special arrangements regarding grades, or adjust grades due to
special circumstances of any kind. Please do NOT ask for any adjustments to your grade (other than for errors in
grading).
Calculators: You are strongly encouraged to use a hand calculator for your assignments and
during exams. I would prefer you spend your time developing an understanding of the statistical
concepts than adding and dividing by-hand. A simple calculator that adds, subtracts, divides,
multiplies, and takes square roots is all you need. You must show your work on all assignments
and exams. Thus, calculators that also do statistical calculations will be of little help (they could
even hurt—sometimes the way they compute things is different from the method you will learn).
Calculators will be allowed for exams, but they must not be part of a phone or any other
electronic device that can store data, connect with the Web, or communicate with others (such as
by text or email).
A note on how to succeed in this course:
You do not need to have the intellectual capacity of Einstein to be successful in this course. The
course does not emphasize mathematics; there will be many calculations, but these require
nothing more than elementary algebra. The emphasis, instead, is on understanding the logic of
the statistical methods. However, effort, vigilance, and a positive attitude will be essential for
success and appreciation of the material. “A” students typically report preparing for exams at
least 2 weeks ahead of time and begin drafting their final papers 4 weeks ahead of time. Gradefocused conversations are welcome when they are proactive (still enough time in the course to
impact a grade), realistic (the math adds up), and framed around concrete goals for the course
(needing an A to get into graduate school is not a reason for conversations about grading, but
wanting to achieve content/skill mastery is). If you find yourself falling behind and feel you need
extra attention, you are encouraged to use the services of the Student Learning Center (SLC),
http://slc.berkeley.edu, where you can seek the additional support needed to reach your course
goals.
Methods of learning:
1. Reading the assigned material, which includes following the numeric examples closely and
writing down questions about anything not entirely clear to you. Reading statistics requires close
study and re-reading, not just reading through once as you might an ordinary book. You will also
find it helpful to complete the How Are You Doing? sections.
2. Completing the any assigned homework. Statistics is a skill— it is necessary to DO statistics,
not just read and understand.
3. Attending lectures, listening closely, asking questions—being sure to have done the reading
first. DON'T fall behind!
4. Attending discussion sections led by GSIs—be sure to bring questions from the reading with
you. This is your chance to get real help with what is not completely clear and to pursue deeply
whatever has excited you. (Yes, there can be exciting things in statistics!)
5. Studying for, taking, and reviewing answers for exams.
6. Testing your knowledge and reviewing lectures using the online supplement, MyStatLab, at
http://www.pearsonhighered.com/aron and http://www.mystatlab.com.
Lecture and Exam Schedule: This lecture schedule is subject to change as needed during the
semester. Lecture slides will be posted in the bCourse before the start of each class. These lecture
slides may be updated after class to reflect needed changes. Readings from the text should be
completed before the corresponding lecture.
Week Date
Topic
Reading
1
Introduction and the Scientific Method
Aron Web ch. 1
2
Research Design in Psychology
3
4
Variables and Displaying Data
Aron ch. 1
Describing Data (central tendency, variability, etc.)
Aron ch. 2
Measures of Variability and the Normal Distribution
Aron ch. 3
Sampling Distributions and Hypothesis Testing
Aron ch. 3
*Hmwk 1 due
*Hmwk 2 due
Exam 1
5
6
7
8
Hypothesis testing and the Central Limit Theorem
Aron ch. 4 (108-120; 125-131)
The Sampling Distribution of the Mean
Aron ch. 5 (139-158)
Z-test, Directional Hypotheses, and Decision Errors
Aron ch. 6 (177-189)
Decision Errors and Power
Aron ch. 6 (189-214)
Power and Effect Size
Aron ch. 6 (214-218)
T-Distribution and One-sample t-Test
Aron ch. 7 (226-240)
Experimental Designs, Dependent t-Test, and Confidence Intervals Aron ch. 7 (240-258);
ch. 5 (158-166)
*Hmwk 3 due
*Hmwk 4 due
*Hmwk 5 due
Exam 2
9
10
11
Independent Samples t-Test
Aron ch. 8;
Aron Web ch. 2
ANOVA Logic and Assumptions
Aron ch. 9 (316-337; 345-348)
ANOVA calculations
Aron ch. 9 (337-345; 349-358)
Factorial Design and Interaction Effects
Aron ch. 10 (377-393)
Interactions and Adding Factors
Aron ch. 10 (393-418);
optional: Aron Web ch. 3
*Hmwk 6 due
*Hmwk 7 due
Exam 3
12
Correlation
Aron ch. 11 (439-450)
13
Correlation and Regression Logic
Aron ch. 11 (451-477);
ch. 12 (493-512)
Prediction and Error
Aron ch. 12 (512-525)
14
Non-parametric Statistics and Chi-Square
15
Chi-Square & General Linear Model
Aron ch. 13 (542-553);
ch. 14 (585-605)
Aron ch. 13 (553-569);
optional: Aron Web ch. 4
Exam 4
17
Final Papers Due at 3pm
*Hmwk 8 due
*Hmwk 9 due
*Hmwk 10 due
CAMPUS POLICIES AND GUIDELINES
1. ACCOMMODATION OF RELIGIOUS CREED
In compliance with Education code, Section 92640(a), it is the official policy of the University of California at Berkeley to permit
any student to undergo a test or examination, without penalty, at a time when that activity would not violate the student's religious
creed, unless administering the examination at an alternative time would impose an undue hardship that could not reasonably
have been avoided. Requests to accommodate a student's religious creed by scheduling tests or examinations at alternative times
should be submitted directly to the faculty member responsible for administering the examination by the second week of the
semester [Sept. 4th, 2014].
Academic Calendar Webpage link
2. CONFLICTS BETWEEN EXTRACURRICULAR ACTIVITIES AND ACADEMIC REQUIREMENTS
The Academic Senate has established Guidelines Concerning Scheduling Conflicts with Academic Requirements to address the
issue of conflicts that arise between extracurricular activities and academic requirements. These policies specifically concern the
schedules of student athletes, student musicians, those with out-of-town interviews, and other students with activities (e.g.,
classes missed as the result of religious holy days) that compete with academic obligations.
-The pedagogical needs of the class are the key criteria when deciding whether a proposed accommodation is appropriate.
Faculty must clearly articulate the specific pedagogical reasons that prevent accepting a proposed accommodation. Absent such a
reason, the presumption should be that accommodations are to be made.
-It is the student’s responsibility to notify the instructor(s) in writing by the second week of the semester [Sept. 4th, 2014] of any
potential conflict(s) and to recommend a solution, with the understanding that an earlier deadline or date of examination may be
the most practicable solution.
-It is the student’s responsibility to inform him/herself about material missed because of an absence, whether or not he/she has
been formally excused.
Academic Senate website link
3. ABSENCES DUE TO ILLNESS
From time-to-time the Academic Senate has issued guidance concerning missed classes and exams due to illnesses such as
influenza advising that students not attend class if they have a fever. Should a student experience repeated absences due to illness,
it may be appropriate for the faculty member to ask the student to seek medical advice. The Senate guidelines advise faculty to
use flexibility and good judgment in determining whether to excuse missed work, extend deadlines, or substitute an alternative
assignment. Only the Committee on Courses of Instruction (COCI) can waive the final exam.
4. READING, REVIEW, RECITATION (RRR) WEEK
The Reading, Review, Recitation (RRR) period before final exams provides students time to prepare for exams, to work on
papers and projects, and to participate in optional review sessions and meetings with instructors. For the coming semester, please
keep these dates in mind: In Fall 2014, classes end on Friday, December 5, 2014. RRR week will take place between the last day
classes (December 5) and the first day of the final exam period (Monday, December 15, 2014).
Detailed, updated guidelines on RRR week activities are available on the Academic Senate web site. The Office of the Registrar
has posted answers to frequently-asked questions about the academic calendar.
5. COMMENCEMENT CEREMONIES AND FINAL EXAMS
Campus policy stipulates that graduation ceremonies must take place after the conclusion of final examinations, with the
exception of professional school ceremonies with graduate students only.