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General Information

About IAT 802 Quantitative Research Methods and Design

or the Craft of Scientific Research

 

Note: this is the former and out-dated website from the 2013 course offering. Please see iSpaceLab.com/Riecke/Teaching/#802 for the latest course offerings and information

 

Course Description & Motivation

Your education, research, and thesis work at SIAT (and beyond) requires you to engage in various forms of doing and communicating research. Moreover, your success at SIAT and beyond will in part be evaluated based on the quality of your own research and communication thereof.

The overarching goal of this course is to help you develop the knowledge & skills essential for conducting proper scientific and quantitative research, as well as critically analyzing, discussing, and communicating it. In sum, IAT 802 is an introduction to experimental design and research methodologies where quantitative approaches are appropriate. There will be particular focus on research design for HCI and the sciences.

Details and further information can be found in the course syllabus available on Canvas.

Course Objectives, Learning Goals & Outcomes

The course structure and teaching/learning activities are designed around the following questions. That is, by actively participating in this course, student should be able to effectively address the following questions and perform the respective tasks:

"What's in it for me"?

Practically speaking, engaging in this course will enable you to

  • no longer fear statistics, but instead appreciate and enjoy the beauty and craft of rigorous scientific research ;-)
  • design, conduct, analyze, write up, present, and discuss your own quantitative (or mixed-methods) research projects
  • tackle your own thesis research projects successfully, by having the most powerful scientific research toolbox at your fingertips
  • have enough skills to continue learning and applying scientific/quantitative research methods properly (the goal of the course is to give you a solid basis in the basic research methods and the skills to keep learning and successsfully applying more advanced ones)

Contact Information

Time & Location

Thursdays, 11:30AM - 2:20PM, in SUR 3260

  • First day of class: 5. September
  • Last day of class: 28. November

Drop-in office hours & stats/software help/feedback: TBD, maybe directly after class

Course Management System: Canvas

login, then go to "iat 802 Fall 2013".

Course Textbooks

Required

  • Field, A., & Hole, G. J. (2003). How to Design and Report Experiments. Sage Publications. ISBN: 0761973834 [get your own copy before the first class - we will go through the whole book]
  • Lehman, A., O’Rourke, N., Hatcher, L., & Stepanski, E. J. (2013). JMP for Basic Univariate and Multivariate Statistics: Methods for Researchers and Social Scientists (2nd ed.). SAS Institute. ISBN 1612906036 (the older version which is fine for the course is also available online through SFU lib)
  • TBD: Open Learning Initiative Statistics (online learning modules, probably with a $25.00 fee. Registration infos will be provided in class / by email) might also be: Statistical Reasoning by CMU OLI (no-login link & outline)

Other Recommended Resources (most on reserve):

  • Evans, A. N., & Rooney, B. J. (2010). Methods in Psychological Research. SAGE. ISBN: 1412977886
  • Field, A., Miles, J., & Field, Z. (2012). Discovering Statistics Using R. Sage Publications Ltd. ISBN: 1446200469
  • Field, A. (2009). Discovering Statistics Using SPSS (Third ed. or later). Sage Publications Ltd. ISBN: 1847879071
  • Cunningham, D., & Wallraven, C. (2011). Experimental Design: From User Studies to Psychophysics (1st ed.). A K Peters/CRC Press. ISBN: 9781568814681
  • Oehlert, G. W. (2000).A First Course in Design and Analysis of Experiments. W. H. Freeman. (.pdf of book and data sets available online)
  • Vogt, W. P. (2006). Quantitative Research Methods for Professionals (1st ed.). Allyn & Bacon .[excellent non-mathematical overview of different techniques incl. complex ones]

Reference Readings:

Statistics explained in simple terms

  • Vickers, A. J. (2009). What is a p-value anyway? 34 Stories to Help You Actually Understand Statistics. Addison Wesley.
  • Motulsky, H. (2010). Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking. Oxford University Press, USA.
  • Urdan, T. C. (2010). Statistics in Plain English, Routledge Academic.
  • excellent free online interactive statistics & probability course from udacity by Sebastian Thrun (allthough rather basic)
  • StatisticsHell: Excellent & humorous statistics resources & online lecture videos by Andy Field

Reference Readings: Advanced & Modern Statistics Methods

  • Wilcox, R. (2011). Modern Statistics for the Social and Behavioral Sciences: A Practical Introduction (1st ed.). CRC Press. ISBN: 1439834563
  • Wilcox, R. R. (2010). Fundamentals of Modern Statistical Methods: Substantially Improving Power and Accuracy (2nd ed.). Springer. ISBN: 1441955240

Scholarly writing

  • Sternberg, R. J., & Sternberg, K. (2010). The Psychologist’s Companion: A Guide to Writing Scientific Papers for Students and Researchers (5th ed.). Cambridge University Press.
  • Field, A., & Hole, G. J. (2003). How to Design and Report Experiments. Sage Publications.
  • Williams, J. M., & Colomb, G. G. (2010). Style: Lessons in Clarity and Grace (10th ed.). Longman.
  • Booth, W. C., Colomb, G. G., & Williams, J. M. (2008). The Craft of Research, Third Edition (3rd ed.). University Of Chicago Press.
  • Boice, R. (1990). Professors as Writers: A Self-Help Guide to Productive Writing. New Forums Press.
  • Stevenson, S., & Whitmore, S. (2001). Strategies for Engineering Communication (International student ed.). Wiley.

Further Reference Readings:

  • Weinberg, G. M. (2001). An Introduction to General Systems Thinking (25 Anv.). Dorset House. ISBN 0932633498
  • “The earth is spherical (p < .05): Alternative methods of statistical inference” by K. J. Vicente & G. L. Torenvliet “Theoretical Issues in Ergonomics Science” (2001); v. 1; pages 248 – 271
  • “You can't play 20 questions with nature and win: Projective comments on the papers of this symposium” (1973) by A. Newell; in W. G. Chase (Ed.) Visual Information Processing; New York: Academic Press; pages 283 - 308

Supplementary readings will be announced as needed

When to use what statistical test?

id

from UCLS, incl. SAS, Stata, and SPSS examples

from Univ. of Delaware

when to use what test

decision tree by Corston & Colman, 2000

decision tree by Neill, 2008, based on Howell, 2008

APA on tests & measures

Statistics Glossary and Terminology

from Glossary of Statistical Terms (U Berkeley)

JMP Resources

Installation instructions: http://www.sfu.ca/itservices/technical/software.html

Online Tutorials to get you started

 

Statistics Applets & Tutorials Collections

onlinestatbook or here

collection of statistics applets

from hope college

Virtual Laboratories in Probability and Statistics

WISE statistics applets & tutorials

from Univ. of New Brunswick

StatPrimer from San Jose State Univ.

Power and Effect Size Calculators

Power and sample size calculator; see also here

Effect size calculator links

Research randomizer: generate random numbers for assigning participants to conditions

[disclaimer: I did not check the correctness of all linked resources]

 

 

Intro

Introduction & Big Picture

Week 1: 2-8 Sept

Learning Goals

What, why, so what? Understand course procedures and "big picture"

  • Understand course structure and teaching/learning activities and find your way through the course
  • Understand Team-Based Learning (TBL), Readiness Assurance Tests (RAT). and JiTT/Warmup exercises: Why do they support effective learning? What's required?
  • Get to know & introduce each other
  • Start thinking about statistics, quant. Research methods, and potential projects
  • Hopefully start getting even more excited about research!
  • Explain relevance of rigorous scientific and quantitative research

In-class Activities: Week 1

Introductions

Pre-questionnaire & student expectations survey

Overview of class structure and teaching/learning activities

demo in-class experiment

Sketching research questions & data plots

Intro to Statistical Packages like JMP using data we collected in-class

Q&A

Preview of what's next

Readings for this week (due before lecture)

Due This Week

Week 1 preparations:

  1. Familiarize yourself with the course management system Canvas: login and find the IAT802 tab
  2. I expect all to have read & understood the IAT 802 Course Syllabus
  3. Acquire required textbook: Field, A., & Hole, G. J. (2003). How to Design and Report Experiments
  4. Install JMP on your computer (if you have a laptop, install it there and always bring it to class)

Week 1 follow-up activity

  1. Start thinking about project ideas, consult your supervisor and/or me if you like
  2. Start thinking about teams (ideally 2 people each)

Preparation for Next Week

Do readings & see "to-do's for week 2" below

 

W2

Intro to scientific Research Methods; Quant vs. qual

Week 2: 9-15 Sept.

Learning Goals

aka: After completing this section, you should be able to do the following:

appreciation of qualitative and quantitative rsearch tools as different, yet equally valid toosl, just for a different purpose and aim.

Compare and contrast quantitative vs. qualitative research methods and their respective strengths and purposes, and have a better idea of which approach is most suitable for what kind of goals and circumstances

Key Concepts

In-class Activities: Week 2

TBL activities

  • iRAT (individual Readiness Assurance Test, a Team-Based Learning approach, see teambasedlearning.org for details)
  • tRAT (team-based Readiness Assurance Test)
  • Peer-review & Discussion
  • Working with project ideas: partner research idea pitch activity
  • [Survey feedback & Q&A if sufficient responses are ]
  • [Working with JMP interface: postponed until next week, when there's more time & Liaqat is back]

Second half of session is jointly with IAT 801: “Quantitative research methods and design” by Thecla Schiphorst: be prepared to ask questions about and discuss different research approaches

Readings for this week

See "to-do's for week 2" in Canvas

 

 

Due This Week

Do readings & see "to-do's for week 2" below

 

Preparation for Next Week

Do readings & see "to-do's for week 3" below

W3

Exp. design, Descriptive Stats, Research Ethics

Week 3:16-22 Sept.

Learning Goals

Key Concepts

aka: you should be able to discuss / explain those terms, and apply them in your own reasearch project

In-class Activities: Week 3 (DRAFT)

  • JiTT / questionnaire feedback
  • Discussion on project proposals
  • Research ethics: Presentation & discussion of Zimbardo's Stanford Prison Experiment & his TED talk on the Psychology of Evil; here's a shorter version
    • > brainstorm potential ethical issue in your own research
  • [time permitting:] Discussion on research ethics, biases etc. using examples:
    • if Prof/TA asks students in course to participate in their exp.
    • using your own family/friends (e.g., advertizing on facebook) for your research
    • in general: why care about research ethics?
  • Discussion of plagiarism (examples: PhD theses)
    • Plagiarism is often a concern for both students and instructors. Read SFU's policy on plagiarism and, in groups of three, discuss whether you think the policy is reasonable and if not, how you would change the policy.

  • [time permitting:] discussion of reading material & reflections

    • example: what's a scientific hypothesis vs. theory? And what's wrong about this explanation

TBL activities

  • iRAT, tRAT, discussion
JMP
  • Demo of how to work with JMP on a given data set, in preparation for:
  • individual / paired iron statistician practice session

Readings for this week

see "to-do's for week 3" below

 

Due This Week

Do readings & see "to-do's for week 3" below

Preparation for Next Week

Do readings & see "to-do's for week 4" below

 

W4

What to Measure? How? With Whom?

Week 4: 23-29 Sept.

Learning Goals

  • Overall: be able to design, conduct, and analyze a simple survey
    • describe and discuss possible issues and limitations of different survey questions / kinds and sampling methods used

Research Proposals

How to come up with a clear & concise idea for research proposal?

how to ensure it's interesting, relevant, doable, and publishable?

 

Key Concepts

In-class Activities: Week 4

  • various organisationsal things
  • Project proposal discussion & peer-feedback activity
  • Iron Statistican Practice session on Descriptive Statistics.

 

Readings for this week

see "to-do's for week 4" below

Due This Week

Do readings & see "to-do's for week 4" below

 

Preparation for Next Week

Do readings & see "to-do's for week 5" below

W5

Inferential Statistics

Week 5: 30 Sept. - 6 Oct.

Learning Goals

Key Concepts

  • Ch. 5: Inferential Statistics

    • Inferential statistics
    • Confidence criterion
    • Sample probabilities: Systematic variation vs. Unsystematic variation
    • Test statistic
    • Statistical significance & inference
    • Type I vs. Type II errors
    • Power (and power analysis)
    • Effect size: e.g.
      • Cohen’s d (t-tests...)
      • r & r^2
      • eta^2 (ANOVA...)
    • Correlation & association
    • One-tail vs. two-tail tests

    Ch. 6: Parametric Statistics

    • Parametric vs. nonparametric tests
    • Homogeneity of variance vs. sphericity
    • t-test test vs. independent t-test vs. dependent t-test
    • ANOVA: one-way vs. two-way

In-class Activities: Week 5

short iRAT/tRAT quiz

activity on 2 versions for research proposals

Feedback on previous iron Stats test

show examples & discuss

irons stats test (paired, ungraded)

simple data plotting & t-test/1-way ANOVA; keep it short to allow for more discussion

time permitting: iron stats peer-evaluation

if there's time left: overview on how to plot/present data

Readings for this week (and the JiTT assignment)

  • Field & Hole: Inferential Statistics (Ch. 5)

  • Field & Hole: Parametric Statistics (Ch. 6) 6.1 - 6.7; later subsections in next week

Video Tutorial: JMP for Students 2: Basic Statistics: watch the whole video

  • JMP book: t-Tests: Independent Samples and Paired Sample (Ch. 7)

  • Task: design simple independent groups experiment that could be conducted as part of this course
  • suggested complementary reading: from OLI Statistical Resoning course, UNIT 4: Inference, Modul 8 & 9, (cf. TOC)

 

Continue brainstorming ideas for your own research project

 

Schedule meeting w/ Bernhard to discuss your research project.

Brainstorm ideas for a small doable experimental research project that you might be able to conduct as part of this course (this can be changed / refined later). Check with your supervisor(s), with us, or anybody else that can guide you. Once you have a first idea of what to do, describe how you would operationalize the variables. Provide a first draft of your

  • Research question(s) and hypotheses
  • Motivation ("why" and "so what")
  • IV (aka predictor variables)
  • DV (aka outcome variables)
  • any control procedures you would need to use

[see JiTT for details]

 

Due This Week

Do readings & see "to-do's for week 5" below

Preparation for Next Week

Do readings & see "to-do's for week 6" below

 

W6

Exp. Design: Dependent & Mixed groups;

Week 6: 7-13 Oct.

Learning Goals

Key Concepts

  • Ch. 6: Parametric Statistics

    • ANOVA: Analysis of variance
    • One-Way Independent ANOVA vs. One-Way Repeated-Measures ANOVA
    • Effect size One-Way ANOVA vs. One-Way Repeated-Measures ANOVA
    • Two-Way Independent ANOVA vs. Two-Way Repeated-Measures ANOVA
    • Effect size Two-Way ANOVA vs. Two-Way Repeated-Measures ANOVA
    • Mixed Anova
    • ANCOVA: analysis of covariance

    JMP book Ch. 8-12:

    • Factorial Designs: Factorial ANOVA vs. MANOVA
    • Nonsignificant interaction vs. significant interaction
    • Assumptions: Between-Subjects Factors vs. MANOVA
    • Univariate vs. Multivariate ANOVA for Repeated-Measures
    Interpretation and reporting of two-way ANOVA results

In-class Activities: Week 6

  • Planning of your presentations for IAT801
  • How to quickly skim papers? (think-pair-discuss)
  • Elevator pitch project presentations (at least for those who's project ideas is well enough developped)
    • in pairs, then a few in front of class (time permitting)
  • Iron statistician activity
    • Plot (descriptive stats)
    • Analyze (inferential stats)
    • Write up (scholarly)

  • TBL activities

    • iRAT / tRAT (TBD)
    • Perform IronStattest on ANOVA. Download the file “Iat802_ironStatsWeek6_YourfirstnameYourlastname”

note: Bernhard out of town this week (conference in Japan)

Readings for this week (and the JiTT assignment)

  • Field & Hole: Parametric Statistics (Ch. 6)

  • JMP book: t-Tests: One-Way ANOVA Between-Subjects Factor (Ch. 8)

  • JMP book: Factorial ANOVA with Two Between-Subjects Factors (Ch. 9)

  • JMP book: Multivariate Analysis of Variance (MANOVA) with One Between-Subjects Factor (Ch. 10)

  • JMP book: One-Way ANOVA with One Repeated-Measures Factor (Ch. 11)

  • JMP book: Factorial ANOVA with Repeated-Measures Factors and Between-Subjects Factors (Ch. 12)

  • suggested complementary reading: from OLI Statistical Resoning course, UNIT 4: Inference, Module 10-12, (cf. TOC)

Due This Week

Do readings & see "to-do's for week 6" below

 

Preparation for Next Week

Do readings & see "to-do's for week 7" below

     

W7

Elevator pitch; 801/802 presentations

Week 7: 14-20 Oct.

Learning Goals

Key Concepts

In-class Activities: Week 7

  • Iron Stats feedback from last week
  • elevator pitch of your research projects: Activity & feedback; be prepared to present (90sec)
  • research proposal activity: probably preparation and discussion of peer-reviewing
  • final discussion of research proposals
    • before submitting for peer review on Sunday night
    • organize peer-review; teams of 3 or 4
    • each person reviews 2 team members
  • [if time left] Iron statistician activity
    • Plot (descriptive stats)
    • Analyze (inferential stats)
    • Write up (scholarly)
  • [if time left] TBL activities
    • iRAT peer review
    • Perform IronStattest on non-parametric. Download the file “Iat802_ironStatsWeek7_YourfirstnameYourlastname”

first joint presentation & discussion session with IAT801 (Qualitative research methods & design) in room 3010

2 presentations from our course in teams of 2-3

  • instructions:Canvas > files > assignments > iat802_ResearchMethodsPresentation.docx

schedule for Thursday Oct 17th, staring at 1pm

1:00 pm to Organize and Review presentation process

Group 1 IAT 801 1:10

Group 2 IAT 802 1:15: Power Analysis | Carolyn Pang, Sujoy Hajra, Emily Cramer

Group 3 IAT 801 1:30

Group 4 IAT 802 1:45: Data Distributions | Drawing Data | Sohail Md, Ethan Soutar-Rau

Group 5 IAT 801 2:00

 

Readings for this week (and the JiTT assignment)

  • Field & Hole: Non-parametric Statistics (Ch. 7)

  • Field & Hole: Choosing Statistical Tests (Ch. 8)

  • JMP book: Measures of Bivariate Association (Ch. 5) - Repeated

  • Review previous reading as needed (especially if the self-test revealed open questions). Most Essential: chapters 4-8, 11, and 13-14 (upcoming); you should really know these things and be ably to apply them

Due This Week

Do readings & see "to-do's for week 7" below

     

Preparation for Next Week

Do readings & see "to-do's for week 8" below

W8

801/802 presentations

Week 8: 21-27 Oct.

Learning Goals

Key Concepts

  • see above

In-class Activities: Week 8

  • TBD:
  • Organizational things…
  • Some stats mnemonics
  • Research Proposal Q&A
  • JMP interactive demo & Q&A session
    • ANOVA flavours, postHoc tests
  • 1pm: Joint research methods presentations w/ IAT801

 

second joint presentation & discussion session with IAT801 (Qualitative research methods & design) in room 3010

3 presentations from our course in teams of 2-3

  • instructions:Canvas > files > assignments > iat802_ResearchMethodsPresentation.docx

schedule for Thursday Oct 24th, staring at 1pm

1:00 pm to Organize and Review presentation process

Group 1 1:10: Correlational Research & Quantitative Survey | Reese Muntean, Xiao Zhang, Xiaolan Wang

Group 2 1:15

Group 3 1:30: t-Test | Srecko Joksimovic, Sanam Shirazi, Xin Tong

Group 4 1:45

Group 5 2:00: Confounds | Mirjana Prpa, Jacqueline Jordan, Ankit Gubta

 

Readings for this week (and the JiTT assignment)

  • Field & Hole: Example of Experimental Write-Up (Ch. 16)
  • Field & Hole: General Points While Writing a Report (Ch. 10)
  • Field & Hole: Answering the Question 'Why?' The Introduction Section(Ch. 11)
  • Field & Hole: Answering the Question 'How?' The Method Section (Ch. 12)

Due This Week

Do readings & see "to-do's for week 8" below

Preparation for Next Week

    Do readings & see "to-do's for week 9" below

     

W9

Doing your own research

Week 9: 28 Oct. - 3 Nov.

Learning Goals

  • Related to Field & Hole: Answering the Question 'What Did I Find?' The Results Section (Ch. 13)

    • Show an understanding of how to provide a rationale
    • Know how to describe previous research and its findings
    • Demonstrate outlining of your own experiment
    • Know how to provide predictions about the experiment's outcome

    Related to Field & Hole: Answering the Question 'Why?' The Introduction Section(Ch. 14)

    • Show an understanding of how to provide a rationale
    • Know how to describe previous research and its findings
    • Demonstrate outlining of your own experiment
    • Know how to provide predictions about the experiment's outcome

    Related to Field & Hole: Answering the Question 'Why?' The Introduction Section(Ch. 15)

    • Show an understanding of how to provide a rationale
    • Know how to describe previous research and its findings
    • Demonstrate outlining of your own experiment
    • Know how to provide predictions about the experiment's outcome

    Related to Field & Hole: Answering the Question 'Why?' The Introduction Section(Ch. 16)

    • Show an understanding of how to provide a rationale
    • Know how to describe previous research and its findings
    • Demonstrate outlining of your own experiment
    • Know how to provide predictions about the experiment's outcome

In-class Activities: TBD

Proposal feedback

Brief iRAT/tRAT quiz

maybe: speed writing & data plotting intro

Interactive demo: non-parametric tests in JMP

TBL activities

  • iRAT & tRAT peer review
  • Perform IronStattest on ANOVA and non-parametric test

 

Readings for this week (and the JiTT assignment)

  • Field & Hole: Answering the Question 'What Did I Find?' The Results Section (Ch. 13)
  • Field & Hole: Answering the Question 'So What?' The Discussion Section(Ch. 14)
  • Field & Hole: Title, Abstract, References and Formatting (Ch. 15)

Due This Week

    Do readings & see "to-do's for week 9" below

     

Preparation for Next Week

Do readings & see "to-do's for week 10" below

 

W10

Getting ready for Running your own Stats

Week 10: 4-10 Nov.

Learning Goals

.

Key Concepts

  • .

In-class Activities

  • JMP: demo of assumption testing for different tests
  • using data visualization/sketching as part of the research process
  • Iron Researcher test on ANOVAs (paired)
  • TBD

open lab: optional JMP tutorial session: Wed 1-2pm, in room SRY 3066

Readings for this week (and the JiTT assignment)

  • see weekly todo list

Due This Week

Do readings & see "to-do's for week 10" below

 

Preparation for Next Week

Do readings & see "to-do's for week 11" below

W11

What does your data tell you?

Week 11: 11 - 17 Nov

Learning Goals

  • being able finish desinging your experiment, and run in properly following ethics standards
  • visualize your data in suitable and effective data plots
  • pick the right statistical analysis tools, perform statistical analysis, and report results in scholarly manner (using APA style for inferential statistics).
  • How to use quantitative & scientific methods properly, carefully & effectively?
    • Experimental design: How to design an effective experiment? What does effective mean?
    • Descriptive statistics: How to present data effectively? What does effective mean?
    • Inferential statistics: What can you conclude from quantitative data? Why? What are your chances of being wrong? How do you decide which statistical methods to use? How to apply them properly? How to do this in a given statistical analysis software?
  • How to communicate scientific research effectively and scholarly?
  • How to critically evaluate and discuss the quality of quantitative / scientific research (of yourself and others)?

In-class Activities: TBD

  • discuss the peer-reviewing system & authorship rules
  • Colloquium presentation: what to focus on; Q&A
  • discussion of final paper expectation and grading rubric: make sure to carefully read iat802_ResearchPaperTemplate_guidelinesAndChecklists.pdf on sakai/resources/assignments/
  • continue the sektch-your-data activity from last week (so please bring any sketches you might already have or did during the last session so you can continue from there)
  • Data analysis Q&A;
  • iron stats Q&A before practice session
  • iron stats practice session (simulation of actual test, ungraded);

Readings for this week (and the JiTT assignment)

  • no dedicated readings to give you more time for your projects. Although reviewing earlier readings and updating notes is always useful ;-)

Due This Week

Do readings & see "to-do's for week 11" below

Preparation for Next Week

Do readings & see "to-do's for week 12" below

 

W12

Iron Stats exam; How to Present Things Scholarly?

Week 12: 18-24 Nov.

Learning Goals

  • How to use quantitative & scientific methods properly, carefully & effectively?
    • Experimental design: How to design an effective experiment? What does effective mean?
    • Descriptive statistics: How to present data effectively? What does effective mean?
    • Inferential statistics: What can you conclude from quantitative data? Why? What are your chances of being wrong? How do you decide which statistical methods to use? How to apply them properly? How to do this in a given statistical analysis software?
  • How to communicate scientific research effectively and scholarly?
  • How to critically evaluate and discuss the quality of quantitative / scientific research (of yourself and others)?

Activities

iron stats graded in-class test

  • this final challenge (aka exam) will be individual, with time limit (probably 60min), and the final results will be a .pdf which is the writeup of the data plotting & analysis + results & discussion section in form of a mini-report; template will be provided

> break <

final project presentation Q&A

summary on using effective illustrations for your paper/presentation

summary on reporting statistics for your paper/presentation

[optional] how to give effective presentations (happy to just send slides…)

Project presentation practice & feedback activity,

 

Readings

  • carefully read iat802_ResearchPaperTemplate_guidelinesAndChecklists.pdf on sakai/resources/assignments/
  • Chapter 5 ("Planning and writing the experimental research paper") from Sternberg, R. J., & Sternberg, K. (2010). The Psychologist’s Companion: A Guide to Writing Scientific Papers for Students and Researchers (5th ed.). Cambridge University Press. (see sakai); feel free to skip 5.1.7 - 5.1.13 & 5.3. make sure to read 5.5 thoroughly.
  • as mentioned earlier, a great annotated sample paper is provided in chapter 16 of Field, A., & Hole, G. J. (2003). How to Design and Report Experiments. Sage Publications. (see sakai / resources / reading material). Check out the results section before the iron stats test for examples how to phrase results in human-readable form.
  • [optional: in case you'd like to read more about scholarly writing and how to improve your writing, I can highly recommend the following books:
    • Sternberg, R. J., & Sternberg, K. (2010). The Psychologist’s Companion: A Guide to Writing Scientific Papers for Students and Researchers (5th ed.). Cambridge University Press.
    • Field, A., & Hole, G. J. (2003). How to Design and Report Experiments. Sage Publications.
    • Williams, J. M., & Colomb, G. G. (2010). Style: Lessons in Clarity and Grace (10th ed.). Longman.

Due This Week

Do readings & see "to-do's for week 12" below

 

Preparation for Next Week

Do readings & see "to-do's for week 13" below

W13

Communicating your research; Colloq presentations

Week 13: 25 Nov. - 1 Dec

Learning Goals

  • How to use quantitative & scientific methods properly, carefully & effectively?
    • Experimental design: How to design an effective experiment? What does effective mean?
    • Descriptive statistics: How to present data effectively? What does effective mean?
    • Inferential statistics: What can you conclude from quantitative data? Why? What are your chances of being wrong? How do you decide which statistical methods to use? How to apply them properly? How to do this in a given statistical analysis software?
  • How to communicate scientific research effectively and scholarly?
  • How to critically evaluate and discuss the quality of quantitative / scientific research (of yourself and others)?

Schedule:

Wed 27th November in SIAT research colloquium, SUR5380: short 5

min) Research Project Presentations for all!

Presentation schedule

...

Presentation rules:

  • strict time limit: 5min/person (we have 15 presentations to go through!)
    • suggestion: 5min presentation + 1 min for questions while the next person is setting things up
  • It'll be graded (10%), see course syllabus
  • Slides will need to be uploaded and tested on presentation computer well before (!) 2:30, probably around 2:15
  • Please add your name & title to sakai wiki / "Colloquium Presentations" to claim your spot and pick the order
  • if you really really cannot attend on that date, email me so we can re-schedule your presentation for one of the remaining classes in week 12 or 13 (please suggest a date)
  • we'll probably do the course evaluations at the end of this session, so please stay around.
  • make sure you uploaded your presentation to dropbox/iat802_finalColloqPresentations and tested on the lectern computer well before the session starts.

 

Presentation samples, mini-paper & discussion

  • Inspiration: check on the web, e.g., Rosling or other TED talks; paper preview presentations in, e.g., Siggraph and other conferences.

mini-paper: What would you like to see in 5min presentation of study/data?

Lecture Activities

  • revision strategies for your writing (lecture + discussion):
  • Peer-reviewing of final papers

joint IAt801/802 celebration in Brew Pub Seating Area with Fireplace, Wednesday Nov 27th from 6:00 - 9:00 pm.

 

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Readings

  • carefully read iat802_ResearchPaperTemplate_guidelinesAndChecklists.pdf on sakai/resources/assignments/
  • Chapter 5 ("Planning and writing the experimental research paper") from Sternberg, R. J., & Sternberg, K. (2010). The Psychologist’s Companion: A Guide to Writing Scientific Papers for Students and Researchers (5th ed.). Cambridge University Press. (see sakai); feel free to skip 5.1.7 - 5.1.13 & 5.3. make sure to read 5.5 thoroughly.
  • as mentioned earlier, a great annotated sample paper is provided in chapter 16 of Field, A., & Hole, G. J. (2003). How to Design and Report Experiments. Sage Publications. (see sakai / resources / reading material). Check out the results section before the iron stats test for examples how to phrase results in human-readable form.
  • [optional: in case you'd like to read more about scholarly writing and how to improve your writing, I can highly recommend the following books:
    • Sternberg, R. J., & Sternberg, K. (2010). The Psychologist’s Companion: A Guide to Writing Scientific Papers for Students and Researchers (5th ed.). Cambridge University Press.
    • Field, A., & Hole, G. J. (2003). How to Design and Report Experiments. Sage Publications.
    • Williams, J. M., & Colomb, G. G. (2010). Style: Lessons in Clarity and Grace (10th ed.). Longman.

Due This Week

Do readings & see "to-do's for week 13" below

Preparation for Next Week

  • Relax & have a wonderful semester break!
  • thanks for all the great projects, suggestions, and feedback!
  • let me know if you have any plans on submitting your project for publicatioun - I'd be happy to support this & help. In a way, that would be the most impressive course outcome if you get to submit your project.
W14

Aftermath

Week 14: 11.-17. April

Learning Goals

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Activities

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Due This Week

  • Relax & have a wonderful semester break!
  • thanks for all the great projects, suggestions, and feedback!
  • let me know if you have any plans on submitting your project for publicatioun - I'd be happy to support this & help. In a way, that would be the most impressive course outcome if you get to submit your project.