Design vs Data
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I developed Design vs. Data for a guest lecture on quantitative research. I decided to focus on the importance of starting with an important question and the value of good design over data collection and statistics.
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Design vs Data
- 2. HELLO Dr. Sara Stetson HELLO My Name Is @GoodCognitions www.sstetson.wordpress.com Dr. Sara Stetson
- 4. Big Ideas Where to start Example of a Big Idea: Tales from the Amazon Quantitative Questions Qualitative Questions Fantastic Variables: and where to find them Study Design 101: Groups and Individuals Design vs. Data: Bad Ideas vs. Big Ideas Qualitative studies I love Quantitative studies I love Start with a Beautiful Question: ?
- 5. Whoever tells the story defines the culture. -David Walsh
- 9. big whale don’t try this
- 10. Fasten here
- 11. OK, so they work
- 12. Not dead yet
- 14. Lace tightly
- 15. Still a bad idea
- 16. good idea
- 17. Nowlet’s talk about Big Ideas…
- 18. Big Idea: Design vs. Data
- 19. Design
- 20. Data
- 21. ideas can be found in…
- 24. A small tribe in the Amazon Pirahã live here
- 25. Pirahã have no fixed numbers. The word that he had long taken to mean “one” (hoi, on a falling tone) is used by the Pirahã to refer, more generally, to “a small size or amount,” and the word for “two” (hoi, on a rising tone) is often used to mean “a somewhat larger size or amount.” --John Colapinto The New Yorker
- 26. Some ideas are just turkeys Pet projects
- 27. Tell me something new about something I care about. -Barbara Frum
- 28. what
- 30. self tipping hat
- 32. Types of Design
- 35. Dogs bark at strangers The dog did not bark at suspect 1 The dog barked at suspect 2 No barks that night Suspect 1 Theory: Observations:
- 39. …A beautiful question shifts the way we think about something and often sets in motion a process that can result in change. Entrepreneurs– or at least the successful ones- do a great job asking beautiful questions…their whole reason for being is to disrupt, innovate, solve a problem no one else is solving --Warren Berger
- 40. Why did the chicken cross the road? What if everyone jumped at once? Is the five- second rule true? Will we ever run out of music? Is your orange the same as my orange? Questions from Vsauce creator Michael Stevens
- 43. Descriptive: describe responses How many, to what extent What is the relationship between… What is the difference in…Comparative:compare groups Predictive: relate variables Independent Variable Changed or controlled by you Dependent Variable The output that is measured Groups Define the groups in the experiment Variables Experimental and control groups
- 44. Fantastic variables & where to find them
- 46. before after Controlled by you
- 48. Output that is measured
- 49. Nominal
- 51. Ratio
- 53. Ordinal
- 54. Worst Better Good Best
- 55. Relationships
- 57. Causal Question: Does Advil work better than a placebo in the treatment of housewife headache? comparative
- 58. Statistics
- 59. Team A Team B AVERAGE RUNNIG TIME = 123 seconds
- 60. 110 111 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 MEAN =123 TEAM A TEAM B
- 61. The Meansquared deviation From the mean….
- 63. RUNNING TIME in seconds Subtract MEAN (123 seconds) SQUARED Deviation 120 3 9 122 1 1 129 -6 36 122 1 1 127 -4 16 122 1 1 120 3 9 MEAN Squared Deviation = 10.42 This is the deviation from the mean Square root of MEAN Squared Deviation = 3.23 TEAM A
- 64. RUNNING TIME in seconds Subtract MEAN (123 seconds) SQUARED Deviation 109 -14 196 111 -12 144 136 13 169 121 -2 4 127 4 16 115 -8 64 130 7 49 MEAN Squared Deviation = 91.71 This is the deviation from the mean Square root of MEAN Squared Deviation = 9.58 TEAM B
- 65. Target Number (Neider, 2004; Neider & Miller, 2003) MEAN HIGH variability LOW variability Different MEAN MEAN Same MEAN TEAM A TEAM B
- 66. Differences
- 67. MEAN 1 MEAN 2 MEAN 1 – MEAN 2Difference between group means Variability of groups SD + SD 2 2 n1 n2 SIGNAL NOISE
- 69. Sampling
- 70. Selection Bias
- 71. Abraham Wald
- 75. The Superintendent holds a “focus group”
- 76. Response Bias
- 77. Army Alpha Test
- 78. lawn tennis, anyone? Great lights, if you can get them From: Gould, 1996
- 87. Time 1 No Treatment Time 2 Treatment Time 1 Treatment Time 2 No Treatment
- 90. Tell a story Build a theory This place, this time…
- 91. Maybe stories are just data with a soul -Bene Brown
- 92. Central Question: Broad question about a central phenomenon What or How Use describe or discover Open-ended Sub-questions: for participants What or how is the… Narrow the focus Story = narrative Meaning of = phenomenology Theory that explains the process of = grounded theory Cultural pattern = ethnography In the case of = case study Cresswell & Plano Clark (nd) Principles of qualitative research: designing a qualitative study, University of Nebraska What happened? = describing What was the meaning to the people = understanding What happened over time = a process In the setting?
- 94. Ethnography
- 95. Some stories enhance life and others degrade it. So we must be careful about the stories we tell. -Burton Blatt
- 99. Setting & Events
- 102. Phenomenological
- 104. If you are one of those who maybe wondered what a WASPkid is, but never took the time to read the little bio on the side of the page, you're about to find out. The very lively lady in the picture above is my remarkable mother. Mom was one of 1,074 women to fly military aircraft during WWII as a member of the Women Airforce Service Pilots (WASP). These amazing women trained to more stringent standards than the men, flew all sorts of non-combat missions.
- 106. Induction
- 107. Grounded Theory
- 109. Design vs. Data (again)
- 111. Why do I love these studies?
- 112. Power of influence…
- 114. 24 aggressive role model 24 passive role model 24 control- no role model Female model Male model No Model Male model Female model No Model 6 boys 6 girls The design 72 children Groups matched on level of aggressiveness
- 116. Power of Conformity
- 117. Male actor Male actor Male actor Male actor Male actor Male student Male actor Male actor participant actors Perceptual task Trial 1 = correct Trial 2 = correct Trials 4 - 18 = 11 incorrect Trial 3 = incorrect Interviews
- 118. Asch,1940
- 122. Cycletheives Nettle & Nott, 2012
- 123. We are watching you
- 125. Power of observation
- 126. Observer Observer Observer Field Notes TIME ACTIVITY AUDIENCE SOURCE 13 school systems 24 classrooms
- 127. Observer Observer Observer Field Notes COMPREHENSION: instruction Use this category whenever a teacher does/says something to help one or more children understand or work out the meaning of more than a single word. COMPREHENSION: prediction If a teacher says something like, "Now that you've read the first part of the story, what do you think is likely to happen in the next part?" the behavior goes here. COMPREHENSION: preparation This includes everything a teacher does to prepare for reading before it begins. The category thus covers attention to new vocabulary. … Or to provide them with background information… (Examples of codes)
- 130. What?
- 131. The door study
- 132. Simons & Levin, 1999
- 133. I would know you anywhere 6.4 6.6 6.8 7 7.2 7.4 7.6 7.8 8 8.2 Category 1 7 people 8 people 50%
- 134. Power of emotion Klin et al., 2002
- 136. 15 autistic participants 15 matched controls 5 video clips RATER 1 RATER 2 4,860 Frames mouth eye object
- 137. Matched controls
- 138. Matched controls
- 139. The upper and lower boundaries of boxplots are the 25th and 75th percentiles. The horizontal line marks the median of the distribution, and the vertical lines above and below the box extend to the minimum and maximum. Really big difference
- 140. Power of intuition
- 141. Judginga leader Ambady & Rule, 2008
- 142. I look powerful I look weak
- 143. 50%
- 144. 1 2 3 4 5 6 7 TRAIT RATINGS GLOBAL LEADERSHIP RATINGS competence dominance likability facial maturity trustworthiness Random Blocks
- 145. Perception of POWER = Company Profit
- 146. Nice guys vs. bad boys
- 147. Carey Hollywood, CA Hiking, making movies, hanging out, listening to music… Are you interested in having a good time? I am attractive, fairly fit, and am looking for something without a lot of mind games. Life is short, so I want to enjoy it as much as possible. I’m pretty adventurous and willing to try… (Barclay, 2010) Volunteering at food bank and group home AND help others enjoy it
- 148. Control AdvertisementsExperimental Advertisements Add 10% words 1 hobby 1 “self report” 145 college students No information about altruism Long Term Short Term Long Term Short Term Counterbalanced (Barclay, 2010)
- 149. Attractiveness ratings equal to the median for sex Women = 8.0 Men = 8.3
- 150. Short Term Short Term Long Term Long Term Short Term Short Term Long Term Log Term Short Term Short Term Long Term Long Term Short Term Short Term Long Term Long Term Pictures paired with descriptions--Counterbalanced
- 151. Short Term Short Term Long Term Long Term Short Term Short Term Long Term Long Term Short Term Short Term Long Term Long Term Short Term Short Term Long Term Long Term Random Assignment
- 152. Women want to date altruists Men don’t care Men don’t want altruists for 1 night stands Men and women prefer altruists for friends Men and women prefer to loan money to altruists Women do Men and women prefer altruists for relationships
- 153. Are we done yet?