PSY 392: Data Mining

Fall 2019
MWF 9:30 am - 10:20 am
PSYCH, Room 3102

Notes

• December 12: The final exam has been graded. You can see a PDF listing of grades. Here, each student has their grades in a row, with the first column indicating the STATLAB ID. If you want specific feedback on the grading of the final exam, contact Dr. Francis or Garrett for details.
• December 3: Details on the final exam are provided below.
• October 21: The midterm has been graded and handed back in class today. If you did not get your exam you can see Dr. Francis during office hours or at the next class period. I took the current grade for the mid-term, homework, STATLAB, and attendance and computed an estimated grade for the end of the semester. You can see a PDF listing of grades. Here, each student has their grades in a row, with the first column indicating the STATLAB ID. A few things of note:
  • Scores on the midterm ranged from quite good to terrible. Students not satisfied with their performance should see Dr. Francis or Garrett to see how to do better.
  • Scores on the homework are rather low. We can help with the homework. Please stop by during office hours.
  • Scores on STATLAB are quite low for some students. These labs are almost "gimme" points. All you have to do is complete the assignment by the due date. We can help if you do not know what to do.
  • Everyone gets 6 absences without penalty. No one is yet beyond that threshold, but some students are close. I don't see how you can hope to pass this class without regular attendance.
Professor


Greg Francis

PSYCH 3186

494-6934

gfrancis@purdue.edu

Office hours: Monday, Wednesday and Friday 3:00-4:00 pm

I check my email frequently, feel free to use it for questions and setting up appointments. If you cannot make my office hours, we can schedule for another time.

Class home page
The Internet home page for this course is http://www.psych.purdue.edu/~gfrancis/Classes/PSY392/indexF19.html This class does not use Blackboard.

Texts
Understanding Statistics and Experimental Design (USED). This book is open access, so you can download a PDF copy for free. If you wish, you can purchase a softcover copy of the book. We will supplment this book with additional readings as we go through the semester.

Learning Statistics with R (LSR). This free PDF is a draft of book. The focus is on learning statistics with the R programming language.

Homework
The first homework is provided in the schedule below. It is in an R file, so you can load it into the text editor you use for R.

StatLab assignments
Some assignments will use a web site called StatLab Online. Step-by-step instructions are in the syllabus along with a unique registration code that you use to set up your StatLab account. The labs are simple experiments that are run through the Internet and can be carried out at any computer lab on campus or at a home computer. At the end of each experiment you will need to calculate statistics that are appropriate for the experimental results. You get credit by finishing the experiment and answering all of the statistics questions correctly. Sometimes, I will also ask you to do similar calculations in R. You will find that computing the statistics is sometimes easiest if you copy and paste the data into a spreadsheet such as Microsoft Excel. If you have not previously used Excel, you may want to look over a tutorial to get started. Sorting is especially useful, and unfortunately is not covered in the previous tutorial. Some of the online calculators can also be useful.

Class attendance: Your presence for the lectures is mandatory, and will be checked each class period. Over the course of the semester, each student may miss up to 6 lectures without penalty. Additional absences will proportionally reduce your class attendance score. Athletes and other special cases need to contact Dr. Francis.

Examinations
There will be a midterm and a final exam.

Grading: Different components of the course will contribute individual scores that are then combined to make your class score. Letter grades are on a straight scale (no rounding). The components contribute as:

Component	Percent weight
Homework	25%
STATLAB	15%
Attendance	5%%
Midterm exam	20%
Final exam	20%
Project	15%



Project: Project, as PDF. I created R code, ComputePower.R, that helps compute power for different statistics. I think for this project, it is easier to use than a lot of other power calculators. Go to the on-line spreadsheet to identify which paper you will use for your project. Here are links to the papers that you can use for your project.

1. Gino, F. & Mogilner, C. (2013). Time, money, and morality. Psychological Science, 25(2), 414-421. PDF
2. Kenrick, A. C., Sinclair, S., Richeson, J., Verosky, S. C., & Lun, J. (2016). Moving while black: Intergroup attitudes influence judgments of speed. Journal of Experimental Psychology: General, 145(2), 147-154. PDF
3. Kilduff, G. J., Galinsky, A. D., Gallo, E. & Reade, J. J. (2019). Whatever it takes: Rivalry and unethical behavior. Academy of Management Journal. PDF
4. Nielson, L. D. & Morrison, E. L. (2005). The symptoms of resource scarcity: Judgments of food and finances influence preferences for potential partners. Psychological Science, 16(2), 167-173. PDF
5. Ongchoco, J. D. K. & Scholl, B. J. (2019). How to create objects with your mind: From object-based attention to attention-based objects. Psychological Science, 30(11), 1648-1655. PDF
6. Rhodes, M., Leslie, S-J., Yee, K. M. & Saunders, K. (2019). Subtle linguistic cues increases girls’ engagement in science. Psychological Science, 30(3), 455-466. PDF
7. Risen, J. L. & Gilovich, T. (2019). Why people are reluctant to tempt fate. Journal of Personality and Social Psychology, 95(2), 293-307. PDF
8. Rounding, K., Lee, A., Jacobson, J. A. & Ji, L-J. (2012). Religion replenishes self-control. Psychological Science, 23(6), 635-642. PDF
9. Sagioglou, C. & Forstmann, M. (2013). Activating Christian religious concepts increases intolerance of ambiguity and judgment certainty. Journal of Experimental Social Psychology, 49, 933-939. PDF
10. Xu, A. J., Schwarz, N. & Wyer, R. S. (2015). Hunger promotes acquisition of nonfood objects. Proceedings of the National Academy of Sciences, 112(9), 2688-2692. PDF
11. Zhu, M., Yang, Y., & Hsee, C. K. (2018). The mere urgency effect. Journal of Consumer Research, 45, 673-690. PDF

I prepared slides for a similar type of paper. You might find it useful as a template for your own presentation.



Final exam: You can download a pdf copy of the final exam. The exam refers to two files that you use.
• Lazareva et al, 2005
• SenseOfHumor.xlsx


Teaching Assistant


Garrett O'Day

PSYCH 3194

goday@purdue.edu

Office hours: Monday 12-1 pm in Hillenbrand Hall (Room C102); Wednesday and Friday 10:30-11:30 am in PSYCH 3194



Schedule
The schedule will be developed as the semester proceeds. The links to notes with each topic correspond to slides that were (or will be) used during the class.

SCHEDULE
Date	Topic	Reading	Assignments
August 19	Planning
August 21	Probability (notes)
August 23	Probability (notes)	USED: Chapter 1
August 26	Distributions (notes1, notes2)		STATLAB - Speeded Reaction Time (class data)
August 28	Mean and standard deviation (notes1, notes2)		STATLAB - Weber's Law
August 30	Normal distribution and Percentiles (notes1, notes2)
September 2	Labor Day (No class)
September 4	Normal distribution and Percentiles		STATLAB - Memory Span
September 6	Computing in R		Homework 1 (due date changed to Sep 11), answer key
September 9	Normal distribution and Percentiles (notes, extra)
September 11	Signal Detection Theory (notes)	USED: Chapter 2
September 13	Signal Detection Theory (notes)		Homework 2 (updated at 1 pm, on September 9), answer key
September 16	Underlying Distributions (notes)
September 18	Sampling Distributions (notes)
September 20	Hypothesis Testing of a Mean (notes, notes)	USED: Chapter 3
September 23	Power for Hypothesis Testing of a Mean (notes)
September 25
September 27			Homework 3
September 30	Exploring the t test in R (code)
October 2	Multiple testing (code)
October 4	Hypothesis testing of two means (notes)	USED: Chapter 4
October 9	Hypothesis testing of two means (notes)
October 11	ANOVA (notes)		Homework 4, STATLAB - Ebbinghaus Size Illusion
October 14	ANOVA contrasts (notes)	USED: Chapter 6	STATLAB - Judging Faces
October 16	ANOVA power (notes)	USED: Chapter 7	STATLAB - Emotional Stroop Effect
October 18
October 21	Data Thuggery	GRIM test paper, Mini-GRIM test, Dijksterhuis et al. paper, Dijksterhuis et al. supplement
October 23	Data Thuggery	SPRITE online, Wansink et al. paper, Carter et al. paper
October 25	Data Thuggery	STATCHECK online, Forster & Denzler (2012), Investigation of Forster & Denzler (2012), Data Colada, R code
October 28			STATLAB - Judging Art
October 30	P-hacking (Online app)		STATLAB - Stroop Effect
November 1	P-Curve	R code for p-distributions, Carney et al. (2010), Check risk proportions Spreadhseet, Chi square calculator, Test of two proportions, p-checker app
November 4	slides	USED: Chapters 7 and 9
November 6
November 8	Test for Excess Success slides	USED: Chapters 9 and 10	Homework 5, as PDF
November 11	Test for Excess Success slides	USED: Chapter 11
November 13	Test for Excess Success
November 15	No class
November 18	Test for Excess Success slides	USED: Chapter 12
November 20	Test for Excess Success		Homework 6, as PDF, Sparrow et al. (2011), Huang et al. (2011), STATCHECK online
November 22	Test for Excess Success
November 25	Student presentations		Project, as PDF
November 27	Thanksgiving Break
November 29	Thanksgiving Break
December 2	Student presentations
December 4	Student presentations
December 6	Student presentations
Date	Topic	Reading	Assignments