PSY 3801 Introduction to Psychological Measurement and Data

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PSY 3801 (Lec section 001, Lab sections 002-011)
Introduction to Psychological Measurement and Data Analysis
Fall, 2014
Lectures – MWF, 11:15-12:05, Willey Hall 125
Labs – Tuesdays (see schedule at the bottom of this page)
Course website: Moodle (accessible via MyU)
Course Description: PSY 3801 (4 cr) is an introduction to the basic concepts and procedures related to the measurement and analysis of
psychological variables (subject matter often called Statistics). The main goal of this course is for students to understand the data of
psychology and the appropriate selection and use of statistical tools to describe and evaluate results of psychological research. This
course will fulfill the University’s Liberal Education Requirement in Mathematical Thinking and provides the quantitative foundations
for PSY 3001W: Intro to Research Methods, and PSY 3902W: Major Project in Psychology. This course will also prepare you to
understand research results presented in future Psychology courses and to participate in faculty research projects.
Prerequisites: Knowledge of math through high school algebra; PSY 1001 (Intro Psychology).
This course is designed to meet two of the seven Undergraduate Student Learning Outcomes:
In order to successfully complete this course, you must demonstrate that you:
- Can identify, define, and solve problems.
- Can locate and critically evaluate information.
Specific Course Goals:
1. To teach you how to select the appropriate method(s) of data analysis for a given research question.
2. To help you understand the equations that define data analysis concepts in mathematical form.
3. To teach you to identify and select the appropriate computational equations for the relevant methods of data analysis.
4. To teach you how to apply the equations to data to compute appropriate statistics.
5. To teach you to interpret the results for the psychological problem that motivated the analysis.
Required materials:
Textbook: Caldwell, S. (2010). Statistics Unplugged (4th ed.). Wadsworth/Cengage Learning.
Calculator: Sharp EL-243SB (available in the bookstore and online). The calculator itself says SHARP ELSI MATE EL-243S on its
face. This is the ONLY calculator you will be permitted to use during Exams and Quizzes.
Lectures and Textbook Readings:
The textbook will support and supplement the lecture material, so you should refer to the textbook as necessary to understand the lecture
material. Material that is presented on the screen during lectures will be posted at the course website shortly after each lecture.
Instructor: Mark A. Stellmack, Ph.D.
Ways to contact me:
email: stell006@umn.edu (I usually reply pretty quickly.)
phone: 612-625-0501 (You usually will have to leave a message.)
In person at one of my “Student Hours”: Mondays 3:00-4:00, Tuesdays 10:00-11:00, Elliott Hall S105
By appointment: Send me an email or phone me to arrange a time.
LABS – All labs are on TUESDAYS.
Sec
002
003
004
005
006
007
008
009
010
011
Time
9:45-11:00
9:45-11:00
11:15-12:30
11:15-12:30
1:00-2:15
1:00-2:15
2:30-3:45
2:30-3:45
4:00-5:15
5:30-6:45
Room
STSS 512B
STSS 530B
KHKH 2-260
STSS 530A
STSS 432A
STSS 131B
STSS 512A
STSS 432B
STSS 432B
STSS 432A
Section Leader
Amy Shu
Peter Lynn
Pierce Ekstrom
Viann Nguyen-Feng
Sarah Semmel
Jake Appleby
Dominic Mussack
Jordan Beim
Brittany Marcus-Blank
Ohad Szepsenwol
Email
shuxx069@umn.edu
lynnx103@umn.edu
ekstr076@umn.edu
nguy2174@umn.edu
semm0023@umn.edu
apple160@umn.edu
muss0080@umn.edu
beimx004@umn.edu
marcu093@umn.edu
szeps001@umn.edu
Section Leaders’ office hours will be posted on the course web site (Moodle). You may attend any Section Leader’s office hour. You
may ask questions about course material during lectures, labs, or office hours, or you may email questions to me or the Section Leaders.
Tutors: Former PSY 3801 students have volunteered to answer your questions about the course material. If you would like to meet with
a tutor, email me (stell006@umn.edu) the days and times that you have available. I will forward your times to our tutors and if one can
meet with you at one of those times, he or she will contact you directly to make the arrangements.
PSY 3801 Introduction to Psychological Measurement and Data Analysis – Fall, 2014 1
2 WAYS TO EARN POINTS IN THIS COURSE (also see the scorecard on the last page of this syllabus)
(1) Exams:
- There will be 4 non-cumulative exams (each worth 100 points) and a cumulative final exam (150 points).
Thus, it is possible to accumulate 550 points on exams.
- Exams will be based on lecture material and material from the Caldwell text.
- If the instructor determines that there is not enough space in the lecture hall for exams, some students will be
directed to an alternate location for exams. Students will be told where to take the exam via email and during
lecture. YOU MUST TAKE THE EXAM IN THE ROOM TO WHICH YOU WERE ASSIGNED. IF
YOU TAKE THE EXAM IN AN INCORRECT LOCATION, 10 POINTS WILL BE DEDUCTED
FROM YOUR EXAM SCORE.
- Students who arrive late will be able to take the exam, but STUDENTS WHO ARRIVE AFTER THE
FIRST STUDENT HAS FINISHED THE EXAM WILL NOT BE PERMITTED TO TAKE THE EXAM.
- All regularly-scheduled exams will include some combination of multiple-choice questions and written
problems to be solved. (The written problems will involve doing computations, writing your answer, and
showing your work.) Please bring a #2 pencil to exams.
- Bring a photo ID to exams.
- During exams, students will not be permitted to listen to audio reproduction devices (e.g. personal stereos).
Students also will be asked to turn off cell phones and place them out of sight.
- University policy requires that make-up tests be made available in very limited circumstances. Unless your
situation fulfills the criteria outlined by the University, REQUESTS FOR MAKE-UP EXAMS WILL NOT
BE CONSIDERED. The Instructor (Dr. Stellmack) alone will determine whether an absence is legitimate (see
“Legitimate Absences” on page 3). Exams will be given on the dates shown on the attached Schedule (see
pages 5-6).
(2) Lab Points (Quizzes, Lab Activities, and Post-Exam Quizlets):
(a) Quizzes/Lab Activities:
During nine of the labs this semester (Labs 1, 2, 3, 5, 6, 8, 9, 11, and 12), there will be 10 points
available for you to earn. There will be EITHER a 10-point Quiz OR a 5-point Quiz and an additional
5-point activity. The available points will be explained in lab. Note that there will ALWAYS be a quiz
during the labs listed above.
The Quiz system is described in detail on the next page.
(b) Post-Exam Quizlets:
During the remaining labs (Labs 4, 7, 10 and 13), your Section Leader will return the most recent exam
and go over the exam questions and answers to help you prepare for the cumulative Final Exam. After
discussing the exam questions, you will be given a 20-point Post-Exam Quizlet, which will be an
additional opportunity for you to show that you have mastered the course material. The questions on the
Post-Exam Quizlet will cover material from the previous exam that was somewhat more problematic for
students. It will also include computational problems that are more similar to the types of problems you
completed in your homework. You will receive more specific information about the types of problems
that will be on the Post-Exam Quizlet before those lab sessions.
PSY 3801 Introduction to Psychological Measurement and Data Analysis – Fall, 2014 2
Quizzes (and Homework):
Quizzes are intended to test your mastery of the material on a regular basis. Quiz questions will be based on the
homework problems. Completing and understanding the homework should be adequate preparation for the
Quizzes. You should try to work out the homework problems on your own before consulting the answers or
obtaining help from others.
Here are details of how the Quiz system works:
a. At the end of most LECTURES, you will be assigned homework problems. Complete the homework
problems on paper, showing all your work. (If you want to keep a copy of your homework, be sure to
make a copy before you hand it in.)
b. At the start of the next lab (on Tuesday), turn in your homework. Homework will be collected at the
scheduled start time of the lab. Homework will not be graded, but you must turn in your homework or
your Quiz score will not be counted (you will receive zero points for that Quiz). Your homework must
reflect a genuine effort on your part to complete the problems. This is a judgment call on the part of
your lab Section Leader, so show all of your work and make it clear that you attempted to complete the
problems.
c. Take the PRE-QUIZ at the start of the lab. The Pre-Quiz will be given immediately after the
homework is collected. The Pre-Quiz will take approximately 10-15 minutes. (No Pre-Quiz will be
given on the four days when a Post-Exam Assessment will be given.)
d. Turn in the completed Pre-Quiz. Your lab Section Leader will go over the answers to the Pre-Quiz
problems.
e. If you are satisfied with your performance on the Pre-Quiz, you may leave the lab. Your Section Leader
will spend some of the rest of the lab answering questions and presenting examples based on the
homework and material from the previous week’s lectures. (There may be other activities during the lab
which can be completed for additional points. Your Section Leader will specify that during lab.)
f. Take the QUIZ at the end of the lab. Your Section Leader will give the Quiz during the last 10-15
minutes of the lab. The Quiz will cover the same material as (but it will not be identical to) the PreQuiz.
BOTH THE PRE-QUIZ AND QUIZ WILL BE GRADED. THE HIGHER OF YOUR TWO SCORES,
PRE-QUIZ OR QUIZ, WILL BE RECORDED AS YOUR QUIZ SCORE. IT CAN ONLY HELP YOU,
NOT HURT YOU, IF YOU TAKE BOTH THE PRE-QUIZ AND QUIZ.
The Pre-Quiz is an additional opportunity for you to practice the material. Pre-Quizzes are extra opportunities
that are available only to students who attend the regularly scheduled lab sessions. Students with excused
absences from labs will only be allowed to take the Quiz, not the Pre-Quiz.
COMMUNICATION: THE KEY TO KEEPING SMALL PROBLEMS FROM BECOMING BIG
PROBLEMS. If a situation arises for you during the semester that will affect your ability to attend lecture or
lab, notify the Instructor and your Section Leader as soon as possible, preferably BEFORE the lecture or lab that
you will miss.
“Legitimate Absences”: The Instructor (Dr. Stellmack) will decide whether an absence is legitimate based on
the University Senate Policy on Makeup Work for Legitimate Absences (described at
http://www.policy.umn.edu/Policies/Education/Education/MAKEUPWORK.html). The Instructor very rarely
considers absences to be legitimate. Please come to class on the scheduled exam dates and attend lab sessions to
avoid unnecessary conflicts.
PSY 3801 Introduction to Psychological Measurement and Data Analysis – Fall, 2014 3
ADDITIONAL POLICIES AND PROCEDURES
Incompletes (Per CLA Classroom, Grading, and Examination Procedures): A grade of I (Incomplete) will
only be assigned to a student if the student’s coursework is incomplete and (1) the Instructor has a "reasonable
expectation" that the student can successfully complete the unfinished work on his/her own no later than one
year from the last day of classes and (2) the Instructor believes that legitimate reasons exist to justify extending
the deadline for course completion. If a student does not complete the requirements for the course and does not
request an incomplete, a grade reflecting the student's performance in the course will be assigned. The student
and Instructor must fill out a written agreement stating the terms for completion whenever an incomplete is
requested and approved. Students assigned I's must complete the unfinished work by the date agreed upon with
the instructor or, if no date is specified, no later than one year after the last day of final examinations of the term
in which the I is given.
Students with Special Needs (Per CLA Classroom, Grading, and Examination Procedures): Any student with
a documented disability condition (e.g., physical, learning, psychiatric, systemic, vision, hearing, etc.) who
needs to arrange reasonable accommodations should contact the Instructor and Disability Services at the
beginning of the semester.
Student Academic Integrity and Scholastic Dishonesty (Per the Office for Student Conduct and Academic
Integrity): All students enrolled in University courses are expected to complete coursework responsibilities with
fairness and honesty. Failure to do so by seeking unfair advantage over others or misrepresenting someone
else’s work as your own can result in disciplinary action. The University Student Conduct Code defines
scholastic dishonesty as follows: Scholastic dishonesty means plagiarizing; cheating on assignments or
examinations; engaging in unauthorized collaboration on academic work; taking, acquiring, or using test
materials without faculty permission; submitting false or incomplete records of academic achievement; acting
alone or in cooperation with another to falsify records or to obtain dishonestly grades, honors, awards, or
professional endorsement; altering forging , or misusing a University academic record; or fabricating or
falsifying data, research procedures, or data analysis.
Within this course, a student responsible for scholastic dishonesty can be assigned a penalty up to and including
an "F" for the course and a report to the Office for Student Conduct and Academic Integrity.
Student Mental Health and Stress Management (Per the Provost Committee for Student Mental Health): As
a student you may experience a range of issues that can cause barriers to learning, such as strained relationships,
increased anxiety, alcohol/drug problems, feeling down, difficulty concentrating and/or lack of motivation.
These mental health concerns or stressful events may lead to diminished academic performance or reduce a
student's ability to participate in daily activities. University of Minnesota services are available to assist you
with addressing these and other concerns you may be experiencing. You can learn more about the broad range
of confidential mental health services available on campus via http://www.mentalhealth.umn.edu/.
***************************************************************************
***
This syllabus is subject to change at the Instructor’s discretion.
***
***
Changes will be announced during lecture.
***
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The following pages show a rough outline of the topics to be covered each day. We may not adhere
precisely to this schedule of lecture topics, but EXAMS AND QUIZZES DEFINITELY WILL BE
GIVEN ON THE DATES SHOWN.
PSY 3801 Introduction to Psychological Measurement and Data Analysis – Fall, 2014 4
Monday
Week 1
Aug 31Sep 6
9/1: NO LECTURE – Labor Day
9/2: NO LABS
9/3: Why The World Would Be
A Better Place If Everyone Were
Just Like Me (ch. 1)
9/5: Scales of Measurement (ch.
1); Summation Notation
9/8: Basics of Experimental
Design
9/9: Lab 1 – Quiz A
9/10: Measures of Central
Tendency (ch. 2)
9/12: Measures of Variability (ch.
2)
9/17: Probability and Normal
Curves (ch. 3)
9/19: The Standardized Normal
Curve (ch. 4)
Tuesday
Wednesday
Week 4
Sep 2127
9/23: Lab 3 – Quiz C
9/24: More Z-Scores (ch. 4)
Week 5
Sep 28Oct 4
9/29: Sampling (ch. 5)
9/30: Lab 4 –
Post-Exam-1 Quizlet
10/1: More Sampling (ch. 5)
10/3: Confidence Intervals and the
Z-Distribution (ch. 6)
10/6: Confidence Intervals and the
10/7: Lab 5 – Quiz D
t-Distribution (ch. 6)
10/8: Hypothesis Testing (ch. 7)
10/10: Z-tests (ch. 7)
10/13: Decision Errors; SingleSample t-tests (ch. 7)
10/14: Lab 6 – Quiz E
10/15: More Single-Sample Tests
(ch. 7)
10/17: **EXAM 2**
(ch. 5, 6, 7) PLEASE BRING A
PHOTO ID AND #2 PENCIL
10/20: Related-Samples t-test (ch.
8)
10/21: Lab 7 –
Post-Exam-2 Quizlet
10/22: Independent-Samples t-test
(ch. 8)
10/24: Directional/NonDirectional Tests (ch. 9)
Week 6
Oct 5-11
9/22: Z-Scores (ch. 4)
9/26: **EXAM 1**
(ch. 1, 2, 3, 4)
PLEASE BRING A PHOTO ID
AND #2 PENCIL
Week 7
Oct 1218
9/15: Frequency Distributions (ch.
9/16: Lab 2 – Quiz B
3)
Friday
Week 8
Oct 1925
Week 3
Sep 1420
Week 2
Sep 7-13
Week
PSY 3801 Introduction to Psychological Measurement and Data Analysis – Fall, 2014 5
Week 9
Oct 26Nov 1
Friday
10/27: ANOVA (ch. 10)
Week
10
Nov 2-8
Wednesday
11/3: More Main Effects and
Interactions (online chapter S3)
11/4: Lab 9 – Quiz G
11/5: Review for Exam 3
11/7: **EXAM 3**
(ch. 8, 9, 10, online S3)
PLEASE BRING A PHOTO ID
AND #2 PENCIL
Week
11
Nov 915
Tuesday
11/10: Calculating and
Interpreting Two-Way ANOVA
(online chapter S3)
11/11: Lab 10 –
Post-Exam-3 Quizlet
11/12: More Two-Way ANOVA
(online chapter S3)
11/14: The Chi-Square Test (ch.
11)
Week
12
Nov 1622
Monday
11/17: More Chi-Square Test (ch.
11)
11/18: Lab 11– Quiz H
11/19: Review of Linear
Relationships
11/21: Linear Regression (online
chapter S1)
Week
13
Nov 2329
Week
11/24: Correlation (online
chapter S2)
11/25: Lab 12 – Quiz I
11/26: NO LECTURE
Thanksgiving Break
11/28: NO LECTURE
Thanksgiving Break
10/31: More than One IV: Main
Effects and Interactions (online
chapter S3)
12/1: More Correlation (online
chapter S2)
12/2: NO LABS
12/3: Introduction to statistical
software
12/5: **EXAM 4**
(ch. 11, online S3, S1, and S2)
PLEASE BRING A PHOTO ID
AND #2 PENCIL
12/8: Final Exam Preparation:
Review
12/9: Lab 13 –
Post-Exam-4 Quizlet
12/10: Final Exam Preparation:
Come to lecture with questions
12/12: NO LECTURE
Final
Exam
Week
Week
14
Nov 30Dec 6
10/29: More ANOVA (ch. 10)
Week
15
Dec 713
10/28: Lab 8 – Quiz F
**FINAL EXAM**
Thursday, Dec. 18, 1:30 p.m. – 3:30 p.m.
Willey Hall 125
PLEASE BRING A PHOTO ID AND #2 PENCIL
PSY 3801 Introduction to Psychological Measurement and Data Analysis – Fall, 2014 6
PSY 3801 SCORECARD
Exams:
1
2
3
4
Final
Total 1
Total Points
(Total 1 + Total 2)
633-720
619-632
604-618
561-603
547-560
532-546
489-531
475-488
460-474
417-459
< 417
Lab Points:
/ 100
/ 100
/ 100
/ 100
/ 150
/ 550
Percent
(Approximate)
88-100
86-87
84-85
78-83
76-77
74-75
68-73
66-67
64-65
58-63
< 58
Quiz A
Quiz B
Quiz C
Post-Exam-1 Quizlet
Quiz D
Quiz E
Post-Exam-2 Quizlet
Quiz F
Quiz G
Post-Exam-3 Quizlet
Quiz H
Quiz I
Post-Exam-4 Quizlet
Total 2
/ 10
/ 10
/ 10
/ 20
/ 10
/ 10
/ 20
/ 10
/ 10
/ 20
/ 10
/ 10
/ 20
/ 170
Final
Grade
A
AB+
B
BC+
C
CD+
D
F
PSY 3801 Introduction to Psychological Measurement and Data Analysis – Fall, 2014 7
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