Psychology 225: Statistical Techniques

Fall 2018

Course Syllabus

TR 9:00-10:15PM, KUY 306

 

Description: We will cover central tendency, variability, probability, random variables, the normal distribution, sampling distribution, the central limit theorem, confidence intervals/estimation, hypothesis testing (t-tests, correlation and regression, ANOVA, chi-square, etc.), effect size, and Bayesian inference.

 

Student learning outcomes: This course provides an overview of statistics, focusing on their application to psychology. The focus is on how sample statistics support inferences about population parameters. By the end of the course:

1.     Students will be able to describe key statistical concepts (central tendency, variability, law of large numbers, random variable, normal curve, sampling distributions, central limit theorem, estimation, confidence interval, effect size, bayes factor, etc.) and develop a working knowledge of frequentist and Bayesian statistical inference in psychology (Psychological Knowledge)

2.     Students will be able to distinguish strong from weak evidence for (or against) a claim using scientific reasoning; design, conduct, and interpret a replication study. (Scientific inquiry and critical thinking)

3.     Students will be able to apply ethical standards to evaluate psychological science and practice. (Ethical responsibility)

4.     Students will be able to demonstrate effective writing and to interact effectively with others. (Communication)

 

Instructor: Adam S. Cohen

Office: Sakamaki C405

Office hours: by appointment (Tuesday after class is usually best)

Email: If x = cohen9, then x@hawaii.edu (put “psych 225” in the subject line)

*Unless it is a private matter, please include both me and the TA on email.

 

Teaching Assistants: Heewon Kwon

Office: Sakamaki 400-2

Office hours: by appointment

Email: If x = hkwon7, then x@hawaii.edu (put “psych 225” in the subject line)

 

Required reading: Good news: your textbook for this class is available for free online! Go here: www.openstax.org/details/introductory-statistics

 

If you prefer, you can also get a print version at a very low cost. Your book is available in web view and PDF for free. You can also choose to purchase on iBooks or get a print version from OpenStax on Amazon.com. You can use whichever formats you want. Web view is recommended -- the responsive design works seamlessly on any device. If you buy on Amazon, make sure you use the link on your book page on openstax.org so you get the official OpenStax print version. (Simple printouts sold by third parties on Amazon are not verifiable and not as high-quality.)

Introductory Statistics from OpenStax, Print ISBN 1938168208, Digital ISBN 1947172050.

 

With the exception of the first lecture, readings should be completed ahead of time. It is critical that you read ahead of lecture to do well in this course.

 

Additional resources:

          JASP: https://jasp-stats.org/

          JASP is a statistics program. Please download it before the second class.

 

          Seeing Theory: http://students.brown.edu/seeing-theory/

A visual introduction to probability and statistics.” Some of these visualizations will be used in class.

 

R Psychologist: http://rpsychologist.com/tag/visualization

More useful visualizations we will explore during the course.

 

Laptop Policy: Except for in-class demonstrations with JASP, you are encouraged not to use a laptop in class. The reasons for this will be discussed during week 1.

 

Grading:

 

Assignment

Weight

Homework

30%

Exam 1

10%

Exam 2

10%

Exam 3

10%

Exam 4

10%

Exam 5

10%

Exam 6

10%

Exam 7

10%

 

Homework: There are 15 homework assignments. They are due on Tuesdays at the start of class (9:00AM sharp!) with two exceptions noted in the schedule below. Only hard copies will be accepted. Make sure to include first and last name, student number, and chapter # at the top. Important:

·        Illegible homework will receive 0 points.

·        Failure to show work will receive 0 points.

·        A 10% penalty applies each day HW is late. See the FAQ and Advice section for full details about the late penalty.

 

HW labeled as “optional” will not be graded. But the more you practice the better you will do on the HW, if not the course.

 

Exams: There are seven exams. Sounds like a lot but research shows that testing improves learning (why might this be?). This is known as the testing effect; on the virtues of repeated testing, see the FAQ and Advice section below. Exams are cumulative and cover lecture and reading material. You do not want to be late! Once the first exam is turned in, the exam is closed – no new exams will be given out.

 

Make-up exams will not be granted without prior approval from the instructor. No make-up exam is possible for Exam 7 (the “final” exam): If you cannot take Exam 7 when scheduled, you must drop the course.

 

Grade lines

90% ≤ A ≤ 100%

80% ≤ B < 90%

70% ≤ C < 80%

60% ≤ D < 70%

 

+/- Grades: Will be given within 3% of the grade cutoff, lower bound inclusive, upper bound exclusive. For example, an 86.9% is a B, an 87.0% - 89.9% is a B+, a 90.0% - 92.9% is an A-, and a 93.0% is an A. 

 

Requests for accommodation: Any student who feels s/he may need an accommodation based on the impact of a disability is invited to contact me privately. Please come to office hours or make an appointment with me outside of class to discuss potential requests before the first exam. I would be happy to work with you, and the KOKUA Program (Office for Students with Disabilities) to ensure reasonable accommodations in my course. KOKUA can be reached at (808) 956-7511 or (808) 956-7612 (voice/text) in room 013 of the Queen Lili'uokalani Center.

 

Course Schedule

 

Lecture

Date

Topic

Readings (complete before class)

HW (due in class)

week 1

T

8/21

Sampling and Data; Data collection activity

Chapter 1

R

8/23

Sampling and Data; Intro to JASP

 

 

week 2

T

8/28

Descriptive statistics: Shape and central tendency

Chapter 2

Ch 1: 42-89 (even required; odd optional)

R

8/30

Descriptive statistics: Variability

 

 

week 3

T

9/4

Probability

Chapter 3

Ch 2: 74-107 (even required; odd optional)

R

9/6

Exam 1 (Ch 1-2)

 

 

week 4

T

9/11

Discrete random variables

Chapter 4

Ch 3: 66-116 (even required; odd optional)

R

9/13

Discrete random variables

 

 

week 5

T

9/18

Continuous random variables

Chapter 5

Ch 4: 69-111 (even required; odd optional)

R

9/20

Exam 2 (Ch 1-4)

 

 

week 6

T

9/25

Normal distribution

Chapter 6

Ch 5: 72-101

R

9/27

Normal distribution

 

 

week 7

T

10/2

The central limit theorem

Chapter 7

Ch 6: 60-88

R

10/4

Exam 3 (Ch 1-6)

 

 

week 8

T

10/9

Confidence intervals/estimation

Chapter 8

Ch 7: 61-97 (even required; odd optional)

R

10/11

Confidence intervals/estimation

 

 

week 9

T

10/16

Hypothesis testing: One sample comparisons

Chapter 9

 

R

10/18

Exam 4(Ch 1-8)

 

Ch 8: 95-134 (even required; odd optional)

week 10

T

10/23

Hypothesis testing: One-sample comparisons

 

 

R

10/25

Hypothesis testing: Two-sample comparisons

Chapter 10

 

week 11

T

10/30

Hypothesis testing: Two-sample comparisons

 

Ch 9: 62-116 (odd required; even optional)

R

11/1

Exam 5 (Ch 1-9)

 

 

week 12

T

11/6

Election Day

 

Ch 10: 78, 80, 82, 84, 86, 87, 89, 91, 115-123

due Monday 11/05

R

11/8

Hypothesis testing: Multiple-group comparisons

Chapter 13

 

week 13

T

11/13

Hypothesis testing: Regression

Chapter 12

Ch 13: 59-74

R

11/15

Hypothesis testing: Correlation

Chapter 12

 

week 14

T

11/20

Exam 6 (Ch 1-10, 13)

 

 

R

11/22

Thanksgiving

 

 

week 15

T

11/27

Criticisms of NHST and p-values

Effect size and Confidence intervals (revisited)

Cohen (1994)

Ellis (2010)

Ch 12: 57-79

R

11/29

Bayesian statistics: A gentle primer

Excerpt from Brewer

 

week 16

T

12/4

Strengthening NHST and improving statistical practice:

power analysis, preregistration, open science, replication

Preregistration

Open science 1

Open science 2

optional: Spellman, Gilbert, & Corker (2018)

Replication crisis

HW Week 15: Compute confidence intervals for these problems (use the alpha given in the problem; if alpha is not specified, assume alpha = .05):

Ch 9: 75-87,107-115 (odd)

Ch 10: 78, 80, 82, 84, 86, 87, 89, 91, 115-123

Ch 12: none

Ch 13: none

 

Compute effect sizes for these problems:

Ch 9: 75-87,107-115 (odd)

Ch 10: 78, 80, 82, 84, 86, 87, 89, 91, 115-123

Ch 12: 67-71

Ch 13: 64-74

R

12/6

Review

 

 

Exam Period

R

12/13

945-1145AM

Exam 7 (cumulative)

 

 

FAQs and Advice:

FAQs

1.     What should I do if I miss a class?

2.     What should I do if I have to miss an exam because of [a family wedding, vacation plans, or other event scheduled in advance]?

3.     What if I need to miss a lecture/exam/lab for an Official University-Sponsored Event?

4.       What happens if I turn in my assignment one minute past the deadline?

 

Advice

5.     How to (and how not to) write an e-mail to your professor and TAs

6.       When to ask questions over email and when to set up an appointment

7.       Questions you probably should avoid asking your professor

8.     Performance enhancing supplements for learning and remembering

9.     Advice on academic writing

 

FAQs

1.     What should I do if I miss a class?

You should find a classmate willing to lend you their notes and review the material with you. Do this as soon as possible while the material is still fresh in their mind. After meeting with the classmate, if you have questions, I encourage you to set up an appointment with me or the TA. Although we want to help you catch up, please understand that it’s not feasible for us to repeat the class during office hours, so make sure to have specific questions prepared before seeing us.

 

2.     What should I do if I have to miss an exam because of [a family wedding, vacation plans, or other event scheduled in advance]?

If you need to miss an exam because of an event scheduled in advance, you should take the course next semester. Accommodation is provided under extreme and limited circumstances. Medical and family emergencies will be accommodated as long as appropriate documentation is provided (e.g., formal note on letterhead from a physician for medical emergencies or a university counselor for family emergencies). If you miss an exam because of a medical or family emergency, you should contact me by e-mail no later than the day after the exam (for a Thursday exam, notify me on Friday at the latest) to discuss accommodation.

 

3.     What if I need to miss a lecture/exam/lab for an Official University-Sponsored Event?

“For regularly-scheduled events, students are to notify instructors within the first two weeks of the semester. For special events or tournaments, students are to notify their instructors as soon as they learn of the anticipated absence. In both cases, students who must miss class for such events will be responsible for completing all assigned work as expeditiously as possible.” http://www.catalog.hawaii.edu/about-uh/campus-policies1.htm#excused

 

4.     What happens if I turn in my assignment one minute past the deadline?

Doh! One of the most painful, spirit-crushing academic experiences a student can endure! My advice: don’t put yourself in a situation where you could turn in an assignment 1 minute late. Do whatever you need to do to turn it in with plenty of time to spare: pretend the deadline is 5 hours earlier; reward yourself with a cookie for turning it in early; plan something an hour before the paper is due so that you have to get it done well in advance. A 10% penalty applies for every day an assignment is late. Even if the assignment is 1 minute late. Even if it’s for reasons out of your control like the internet going down or your hard drive crashing. So avoid putting yourself in this situation and submit early. That way if any unforeseen things happen, the assignment won’t be late.

 

Advice

5.     How to (and how not to) write an e-mail to your professor or TAs

When you email your professors or TAs, take a minute to think about what you want to say and how you want to say it.

·        Your message should be clear and grammatical.

·        Stylistically, there’s no need to be overly formal, but at the other extreme avoid internet slang (e.g., thx, omg, lol) since some professors care about a minimum level of formality.

·        Before writing your message, read the syllabus and other course material carefully to make sure the information you need isn’t already there.

 

Here are some examples of how to and how not to write an email to your professors and TAs.

 

Example #1: Don’t do this

Hi Professor Cohen,
I was wondering for our Methods course if their are weeks posted as to what chapters in our textbook correlate with the discussions of that weeks lecture.
Thank you so much for your time,
***** *****

What’s the problem with example #1? Besides the sloppy grammar and spelling and the question not being clear, this information can be located in the syllabus.

 

Example #2: Don’t do this

hey prof, is the paper due tmrw? bc i dont understand it, thx.

What’s the problem with example #2? Try to avoid internet slang. But more importantly, ask for support early! We want to help you succeed in this course!

 

Example #3: Do this

Hi Dr. Cohen,

May I look over my exam sometime this week? I’m available any morning before 12:00 PM. Please let know if any of those times work for you.

Thanks,

***** *****

Clear and direct. Not too formal, not too informal. Good job!

 

6.     When to ask a question over email and when to set up an appointment

Sometimes we can provide help over e-mail, but often it’s easier to talk in person. If you have a few questions and they can be answered quickly, e-mail is probably fine. But if your questions require a longer response, then we recommend you set up an appointment to meet with me or the TAs. Our top priority is to help you understand and think about the material, and it’s often more efficient to do that by talking in real-time during office hours than by the brilliantly slow process of exchanging e-mails.

 

Please read the syllabus closely before asking a question via e-mail. Many of the most common questions are answered in the syllabus.

 

7.     Questions you probably should avoid asking your professor

Q1. Is it still possible for me to get [grade]?

Occasionally, a student will send an email that goes like this:

---start of email---

Hi Dr. Cohen,

May I please have your honest opinion regarding whether you think I could end up with a final mark of 75+% in the course if I work hard on [assignments, exams, etc.]? As well, what do you predict to be the likelihood that I will be able to get 75+% at the end of the semester? I have roughly calculated that I would need at least an average grade of 82% on the remaining 60% of the course content.

Thank you very much for your time.

Sincerely,

***** *****

---end of email---

 

Explanation: Please resist the urge to contact me or the TAs about whether it’s possible to get a certain grade. We have too much respect for you to treat you like someone incapable of doing the math and figuring this out for yourself. Beyond that, there’s not much we can say because what grade you actually earn depends on how hard you work, and we can’t predict that. You have control over your performance on the remaining assignments; the TAs and I do not, although we will do whatever we can to help you succeed.

 

Q2. Do we need to know [X] for the exam?

For example:

---start of email---

Hello professor, I have a question from the reader should I memorize this chart?

Thanks,

****** *****

---end of email---

 

Explanation: Out of fairness I can’t provide information to one student that puts them at an advantage relative to other students. But more importantly, this isn’t the right question to ask if you’re preparing for an exam. You’re in college to learn, so ask questions that will help clarify what you don’t know or don’t understand, that way you can do better on the exam by knowing more, not less. Use questions to figure out what you don’t know, not what you don’t need to know.

 

8.     Performance enhancing supplements for learning and remembering

What if you could take a pill that would help you learn and remember better? And what if it were completely safe and legal? Would you be interested in trying it? It turns out there are performance enhancing supplements that on average give you an advantage in learning and remembering, but they don’t come in a pill. They are techniques that cognitive scientists and educational psychologists have discovered that facilitate remembering and learning, and it’s been shown that students who use these techniques on average outperform those who don’t. Here are a few of the ingredients for enhancing academic performance:

a.     The spacing effect: Students who space their studying across multiple sessions outperform students who spend the same amount of time studying in a single session. This isn’t just the obvious recommendation to avoid procrastinating, which has to do with the size of the gap between studying and testing (study -> gap -> test). This is about creating a gap between studying and re-studying (study -> gap -> re-study -> gap -> test). The size of the study-restudy gap, like the size of study-test gap, matters and there’s interesting evidence that a longer study-restudy gap is better than a shorter one (see the papers below for details).

b.     The alternating practice effect: If you’re learning to hit a baseball, is it better to practice hitting a 100 fastballs in a row, a 100 curveballs in a row, and a 100 sliders in a row, or is it better to practice hitting 300 pitches in which the types of pitches are mixed together? There’s evidence that learners who use the second “alternating” or “interleaving” or “mixed” approach, outperform those using the first “blocking” approach. For psychology, if you have a set of practice problems for chapter 1, chapter 2, and chapter 3, it’s better to alternate the problems than block them by chapter.

c.      The testing effect: This one’s on the house. Students who study and take a test score higher on a final test than students who spend the same amount of time just studying before the final test. This is why we have 3 exams throughout the course.

d.     Taking notes with pen and paper vs a laptop: There is evidence that students who take notes with pen and paper show better recall and test performance than students who take notes on their laptop. Students who use pen and paper are more likely to write down notes in their own words and actively process the material, whereas students using laptops are more likely to copy down what the teacher says word-for-word without actively processing the content. See Mueller and Oppenheimer (2014) below for more details and an explanation.

 

References:

Mueller, P. A., & Oppenheimer, D. M. (2014). The Pen Is Mightier Than the Keyboard: Advantages of Longhand Over Laptop Note Taking. Psychological science, v, pp-pp.

This paper reports a set of studies showing that students learn better when taking notes with pen and paper than with a laptop.

 

Rohrer, D., & Pashler, H. (2010). Recent research on human learning challenges conventional instructional strategies. Educational Researcher, 39 , 406–412.

This paper reviews the spacing effect, the alternating practice effect, and the testing effect.

 

http://www.nytimes.com/2014/07/20/opinion/sunday/how-tests-make-us-smarter.html

An article in the NYTimes reviewing the virtues of repeated testing (the testing effect).

 

http://www.nytimes.com/2014/09/07/magazine/why-flunking-exams-is-actually-a-good-thing.html

Another article in the NYTimes on the testing effect.

 

http://www.nytimes.com/2014/11/23/sunday-review/studying-for-the-test-by-taking-it.html

And another article in the NYTimes on the testing effect and mixed practice effect.

 

Other papers of interest on the science of learning:

Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics. Proceedings of the National Academy of Sciences, v, pp-pp.

This paper reports a meta-analysis demonstrating the virtues of being an active learner rather than a passive listener and shows that active learning is more effective than traditional lecturing.

 

Kozhevnikov, M., Evans, C., & Kosslyn, S. M. (2014). Cognitive Style as Environmentally Sensitive Individual Differences in Cognition A Modern Synthesis and Applications in Education, Business, and Management. Psychological Science in the Public Interest, 15, 3-33.

This paper has a section on the “matching hypothesis” (p. 11), the idea that students learn more efficiently when the teaching method matches their learning style (whether you’re a visual learner, auditory learner, etc.). It comes to the surprising conclusion that the evidence for the matching hypothesis is weak. What seems to matter more is a) whether the teaching method matches the material and b) style flexibility, the ability of students to switch between learning styles.

 

9.     Advice on academic writing

Writing is hard. And writing clearly is even harder. Here is a paper I recommend that will help you as an academic writer.

Plaxco, K. W. (2010). The art of writing science. Protein Science, 19, 2261-2266.