1 / 27

PSY 1950

PSY 1950. Delphine S. Courvoisier Harvard University TAs: Stephanie McMains Joseph McIntyre . Potential mistakes (instructor is Swiss). Temple, Bangkok : IT IS FORBIDDEN TO ENTER A WOMAN, EVEN A FOREIGNER, IF DRESSED AS A MAN.

azia
Télécharger la présentation

PSY 1950

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. PSY 1950 Delphine S. Courvoisier Harvard University TAs: Stephanie McMains Joseph McIntyre

  2. Potential mistakes (instructor is Swiss) • Temple, Bangkok : IT IS FORBIDDEN TO ENTER A WOMAN, EVEN A FOREIGNER, IF DRESSED AS A MAN. • Cemetery: PERSONS ARE PROHIBITED FROM PICKING FLOWERS FROM ANY BUT THEIR OWN GRAVES • Restaurant, Switzerland: OUR WINES LEAVE YOU NOTHING TO HOPE FOR. • Hotel, Japan: YOU ARE INVITED TO TAKE ADVANTAGE OF THE CHAMBERMAID. • Hotel, Zurich : BECAUSE OF THE IMPROPRIETY OF ENTERTAINING GUESTS OF THE OPPOSITE SEX IN THE BEDROOM, IT IS SUGGESTED THAT THE LOBBY BE USED FOR THIS PURPOSE. • Airline ticket office, Copenhagen: WE TAKE YOUR BAGS AND SEND THEM IN ALL DIRECTIONS. • Laundry, Rome : LADIES, LEAVE YOUR CLOTHES HERE AND SPEND THE AFTERNOON HAVING A GOOD TIME

  3. Information • Lectures (Mon and Wed 1-2:30, WJH 1305) • Ex-cathedra presentations • Small quizzes • Reading of recent articles • Writing of abstract and methods/results sections • Lab sessions (Tue 5-6:30,WJH 1305) • Learning how to input and analyze data

  4. Information and schedule • Course websitehttp://isites.harvard.edu/k89723 • Reading (compulsory) • Field, A. (2009). Discovering statistics using SPSS (3rd edition). London: Sage. • Reading (non compulsory; good short refresher) • Petrie, S., Sabin, C. (2009). Medical Statistics at a Glance (3rd edition). Sussex: Wiley.http://www.medstatsaag.com/

  5. Exam and grade • 20% participation • 20% exercises • 25% mid-term test • 35% final exam • Mid-term and final exam are an analysis of data given one week before the test, and questions asked on the analysis. • For an example, see folder exam on isites

  6. Lecture 1

  7. Why do you need statistics? • Duh!! To pass the exam • To understand the methods of data analysis used in scientific articles for (applied) psychologists and for researchershttp://www.jsur.org/v1n1p1 • To apply this knowledge to critical reading of scientific articles in your professional life (continued training) • To apply this knowledge to your own research

  8. Top 10 reasons to be a statistician • Deviation is considered normal • We feel complete and sufficient • We are 'mean' lovers • Statisticians do it discretely and continuously • We are right 95% of the time • We can legally comment on someone's posterior distribution • We may not be normal, but we are transformable • We never have to say we are certain • We are honestly significantly different • No one wants our jobs

  9. Structure of an article • Title • Summary (structured) • Body: • Introduction • Methods • Results • Discussion • References Why do the study How was the study done What was observed What does it mean

  10. Goal of statistical analysis • Describe data • Draw general conclusions about the world and its workings

  11. Question • You collect scores on the BDI (a 21-question multiple-choice self-report depression inventory) from a sample of children. In your research: • Depression is a discrete variable • Depression is a continuous variable • Depression is a ratio variable • Depression is an interval variable • It depends on how you think about depression • It depends on how you analyze the data

  12. Constructs and variables • Constructs are theoretical concepts • Variables are the proxy used to measure those constructs

  13. Question • You collect fMRI data from 10’000 individuals on a sustained attention task linked to ADHD, and plot the results (DV = % signal change) in a histogram. The distribution is very close to normal. These results: • provide strong evidence against a dichotomous view of ADHD. • could easily have arisen even if ADHD were a dichotomous phenomenon.

  14. Median vs. mean • Q: If you were to take 10,000 samples of n=25 from the below population and, for each sample, calculate its mean and median, how would the distributions of those two statistics vary from each other • http://onlinestatbook.com/stat_sim/sampling_dist/index.html

  15. Question These distributions differ in: Shape Dispersion Neither shape nor dispersion Both shape and dispersion

  16. Question These distributions differ in: Shape Dispersion Neither shape nor dispersion Both shape and dispersion

  17. Question • Using (http://onlinestatbook.com/stat_sim/sampling_dist/index.html) which of the following statements is true: • When sampling from normal distributions, the median is an unbiased statistic. • When sampling from skewed distributions, the median is a biased statistic. • both a and b

  18. Graphical representations • Histogram (sorted bar chart) • Box-plot • Scatterplot • Principles: • Have a clear visual message • Promote visual comparisons • Don’t cheat (axes, distortions, etc) • Show all the data • High ratio information/ink

  19. mode: 170 mean median Histogram Tendency to use “round” numbers

  20. outliers ¼ 3rd quartile ¼ Inter-quartile range median ¼ 1st quartile ¼ Smallest value Boxplot

  21. 4 equal areas p25 p50 p75 Percentiles and boxplots X

  22. Scatterplot, central tendency and dispersion

  23. Interaction plots

  24. How many statisticians does it take to change a light bulb? • With what degree of certainty do you need to know?

More Related