METHODS (Psych 201 - Chapter 2 - Spring 2014)

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METHODS (Psych 201 - Chapter 2 - Spring 2014)

  1. 1. THIS WEEK’S PLAYLIST 1 Artist Song 1. Weezer Perfect Situation Power of the Situation 2 will.i.am I Got It From My Mama Nature vs. Nurture; Proximal vs. Distal Influences 4. Taylor Swift I Knew You Were Trouble Hindsight Bias 5. Bill Withers Lean On Me Collectivist Cultural Values 6. Haddaway What Is Love? Operationalizing Constructs 7 Notorious B.I.G. Mo Money Mo Problems Understanding Correlations
  2. 2. SOCIAL PSYCHOLOGY: Introduction and Methods
  3. 3. METHODS: OVERVIEW ! ○ Why do social psychologists do research? ! ! ! ○ How do social psychologists test ideas? ! ! ! ○ What are useful concepts for understanding research?
  4. 4. WHY DO SOCIAL PSYCHOLOGISTS 
 DO RESEARCH?
  5. 5. FOLK WISDOM “The whole of science is nothing more than the refinement of everyday thinking.”
  6. 6. FOLK WISDOM ! ○ A “common-sense,” intuitive explanation for behavior ! ○ Some folk theories are correct, but... Do birds of a feather flock together, or do opposites attract?
  7. 7. FOLK WISDOM ! ○ A “common-sense,” intuitive explanation for behavior ! ○ Some folk theories are correct, but... Does absence make the heart grow fonder, or out of sight, out of mind?
  8. 8. FOLK WISDOM ○ Role of psychology ● When do certain “correct” folk theories apply? ● Why does this happen? ! ○ Many unexpected influences on behavior ! ○ Must empirically test theories to avoid biases ● Importance of the scientific method! ! ○ Dan Simons debunks some folk theories ● http://www.youtube.com/watch?v=5YPiVSdh- RY&feature=mh_lolz&list=HL1314121729
  9. 9. HOW DO SOCIAL PSYCHOLOGISTS 
 TEST IDEAS?
  10. 10. MEASUREMENT ! ○ If a chemist wants to measure a certain reaction, he/ she knows exactly what to do & what to measure. ! ! ○ With psychology, it’s a little less obvious... ● How exactly do you measure self-esteem? ● How exactly do you measure happiness?
  11. 11. MEASUREMENT ! ○ Operationalization ● Wikipedia: “The process of defining a fuzzy concept so as to make the concept clearly distinguishable or measurable and to understand it in terms of empirical observations.” ! ! ○ Now you will try operationalizing something...
  12. 12. LET’S SAY YOU WANT TO STUDY 
 THE EFFECTS OF DRINKING ON DRIVING... ○ You can’t bring a bunch of students into the lab, get them drunk, and have them drive around on Green Street. ! ● You might get in some trouble. Maybe. ! ○ You have to get creative & think of a way to “get at” your question. ! ● Why would drunk people have trouble driving? ○ Poor motor control ! ○ Are there safer (and more legal) ways for you to study the effects of drinking on motor control so you can get at this question a different way?
  13. 13. ONE GROUP OF RESEARCHERS USED...
 HANDWRITING!
  14. 14. SURE, THIS DOESN’T REFLECT 
 LITERAL DRIVING ABILITY...
  15. 15. ...BUT WOULD YOU WANT THIS GUY TO BE RESPONSIBLE FOR DRIVING YOU HOME?
  16. 16. ○ Operationalization ● How to measure an abstract idea in an observable way. ● Spells out exactly how the concept will be measured ! ! ! ! ! ! ! ○ Example: Aggression ● How many times do you punch a doll in front of you? ● How much does your blood pressure rise? ● How long does it take before you yell at someone?
  17. 17. WHAT IS LOVE?
 ! You are conducting a study, and you need to measure how much someone experiences love. ! In order to do this, you need to first operationalize the “fuzzy concept” of love. Baby, don’t hurt me. Don’t hurt me. No more.
  18. 18. WHAT IS LOVE?
 Physiological Angelina might operationalize her love for Brad as how much her heart races, her palms sweat, and her stomach gets butterflies when she sees Brad.
  19. 19. WHAT IS LOVE?
 Behavioral My very fat cat Mason might operationalize love as how much food and how many pets I give him
  20. 20. WHAT IS LOVE?
 Self-Report (Open-Ended) Noah and Allie might operationalize love with a complicated, long-winded answer... ! Fighting, calling each other out on things, but wanting to do that every day & not with anyone else. ! Not easily measured by a “scale.” http://youtu.be/VHqU7L1rVFI?t=2m
  21. 21. WHAT IS LOVE?
 Self-Report (Closed-Ended) ...or, you could just shush them and make them circle a response for how much they love each other on a scale of 1 to 5. http://youtu.be/VHqU7L1rVFI?t=2m
  22. 22. TYPES OF RESEARCH ○ Correlational ● Measuring the relationship between X and Y ! ! ○ Experimental ● Designing an experiment to figure out if X causes Y ! ! ○ Note: Experiments can still involve correlations. The difference is whether you are simply measuring variables to get this correlation, or if you are designing an experiment to test your question.
  23. 23. CORRELATIONAL VS. EXPERIMENTAL ○ Measure 2+ variables; no variables are manipulated ! ○ Measured as they occur in the “real world.” ! ○ No assignment to levels of a variable ○ Measure 1+ variable(s), manipulate 1+ variable(s) ! ○ Experimenters set as a “control condition.” ! ○ Random assignment to levels of the manipulated variable Correlational Experimental
  24. 24. DO VIOLENT VIDEO GAMES CAUSE AGGRESSION? ● Follow 100 kids for 1 week. ! ● Measure how many hours they spend playing violent video games. ! ● Measure how many acts of aggression each kid performs. ! ● At the end of the week, compute a statistical correlation between hours of violent gaming and number of aggressive actions. ○ Randomly assign 5 groups of 20 children to play 0, 5, 10, 15, or 20 hours of violent games for 1 week ! ○ Measure how many acts of aggression each kid performs. ! ○ At the end of the week, the researchers compute a statistical correlation between hours of violent gaming and number of aggressive actions. Correlational Experimental
  25. 25. DO VIOLENT VIDEO GAMES CAUSE AGGRESSION? ● Follow 100 kids for 1 week. ! ● Measure how many hours they spend playing violent video games. ! ● Measure how many acts of aggression each kid performs. ! ● At the end of the week, compute a statistical correlation between hours of violent gaming and number of aggressive actions. ○ Randomly assign 5 groups of 20 children to play 0, 5, 10, 15, or 20 hours of violent games for 1 week ! ○ Measure how many acts of aggression each kid performs. ! ○ At the end of the week, the researchers compute a statistical correlation between hours of violent gaming and number of aggressive actions. Correlational Experimental
  26. 26. DO VIOLENT VIDEO GAMES CAUSE AGGRESSION? ● Follow 100 kids for 1 week. ! ● Measure how many hours they spend playing violent video games. ! ● Measure how many acts of aggression each kid performs. ! ● At the end of the week, compute a statistical correlation between hours of violent gaming and number of aggressive actions. ○ Randomly assign 5 groups of 20 children to play 0, 5, 10, 15, or 20 hours of violent games for 1 week ! ○ Measure how many acts of aggression each kid performs. ! ○ At the end of the week, the researchers compute a statistical correlation between hours of violent gaming and number of aggressive actions. Correlational Experimental
  27. 27. STATISTICAL CORRELATION ○ Correlation Coefficient: A statistical value that indicates how well you can predict one variable using another ● A number between -1.00 and +1.00 ! ○ All of these correlation coefficients COULD have come from a correlational design or an experimental design. ! ○ Also... CORRELATION DOES NOT IMPLY CAUSATION! ● The ability to say one variables CAUSES the other comes from the type of research design, not the type of results
  28. 28. UNDERSTANDING CORRELATIONS ○ Magnitude ● The size of the correlation ● 0.8 is “stronger” than 0.2 ○ Correlation between coffee consumption and exam grade: 0.8 ○ Correlation between water consumption and exam grade: 0.2 ○ Coffee & grades have a stronger correlation than water & grades ! ○ Direction ● Whether the correlation is positive or negative ● -0.8 is negative; 0.8 is positive ○ Correlation between coffee consumption and exam grade: 0.8 ○ Drinking more coffee is related to HIGHER exam grades ○ Correlation between coffee consumption and exam grade: -0.8 ○ Drinking more coffee is related to LOWER exam grades
  29. 29. UNDERSTANDING CORRELATIONS ! ○ Magnitude ● How strong is the relationship? ● How closely are the two variables related to each other? ● Doesn’t matter if one goes up when the other goes down. ! ! ○ Direction ● Do the variables go in the same direction (as one gets bigger, the other gets bigger) or the opposite direction (as one gets bigger, the other gets smaller)?
  30. 30. CORRELATIONS Correlation does not imply causation!! (http://www.youtube.com/watch?v=lbODqslc4Tg)
  31. 31. THINKING ABOUT CORRELATIONS ! ! Reverse causality ! X may cause Y ! Y may cause X ! ! ! Third variable problem ! X and Y may BOTH be caused by some unmeasured variable
  32. 32. THINKING ABOUT CORRELATIONS
  33. 33. THINKING ABOUT CORRELATIONS
  34. 34. THINKING ABOUT CORRELATIONS
  35. 35. THINKING ABOUT CORRELATIONS
  36. 36. CAUSALITY ! ○ We should only make causal claims (“x causes y”) if we have conducted an experiment that includes: ● Manipulation of independent variables ● Random assignment ● [Control conditions] ! ○ These factors take care of concerns with both reverse causality and the third variable problem
  37. 37. CAUSALITY ○ Even if we believe a causal link exists, we can’t take evidence from a correlational design as proof. ● Saying we can’t show causation with a correlational study is different than saying the causal link does not exist!!! ● It may exist, but we are obligated to provide solid, persuasive evidence to show that it does. ● Correlational study designs simply don’t meet that standard – they leave room for too many alternative explanations. ! ○ Social psychologists generally prefer experimental research designs because they establish causality.
  38. 38. The Notorious B.I.G. claims that there is a positive correlation between mo’ money and mo’ problems. ! Can we assume causality here?
  39. 39. MO’ MONEY, MO’ PROBLEMS. ○ Having more money could cause someone to have more problems ○ Having more problems could cause someone to want to make more money ○ Jay-Z Corollary: A romantic relationship could affect the two variables in no fewer than 99 ways. ○ Randomly assign one group to get a lot of money, and one group to be broke ○ Because it is randomized, you assume the two groups are equal in ALL WAYS other than amount of money ○ If there is still a difference in the number of problems, you can conclude that the money caused them. Correlational Experimental
  40. 40. THINKING ABOUT CORRELATIONS
  41. 41. EXPERIMENTAL DESIGN ○ Independent variable (IV) ● The variable that is manipulated by the researcher ● The IV is hypothesized to cause changes in the DV ● Assignment to different levels of the IV must be random! ! ! ○ Dependent variables (DV) ● The variable that is measured – behavior, thoughts, outcomes. ● In social psych, the DV is almost always “average behavior” when we look across all individuals in a condition
  42. 42. EXPERIMENTAL DESIGN ○ Control condition (CC) ● A group assigned to some “inherently meaningful” level of an IV… often “0” (the absence of the IV), but sometimes not ● Used as the comparison group ● Example: Mo’ Money, Mo’ Problems ○ Control Group = Broke ! ! ○ Random assignment ● Assigning participants to different groups, so they are just as likely to be placed into one group as into another ● For us, this “cancels out” personality – allows us to focus on the manipulation/environment
  43. 43. EXPERIMENTAL DESIGN ○ Random assignment to a manipulated independent variable (IV) is the hallmark of experimental design ● This ensures that individuals are evenly distributed across conditions (it “cancels out” differences between subjects) ! ○ This allows us to conclude that different levels of the IV actually cause differences in the DV ● No longer need to be worried about reverse causality because we changed one variable before measuring the other ● No longer need to be worried about third variable problems
  44. 44. MORE ON EXPERIMENTAL DESIGN ○ Hypothesis: Giving a public speech temporarily increases extroversion Extroverts Introverts Initial group Give speech Control condition
  45. 45. MORE ON EXPERIMENTAL DESIGN ○ Without Random Assignment: Give speech Control condition
  46. 46. MORE ON EXPERIMENTAL DESIGN ○ With Random Assignment: Give speech Control condition
  47. 47. MORE ON EXPERIMENTAL DESIGN ○ Does random assignment solve all of our concerns? ● No! ● You can still get biased samples for various reasons ● It’s important to replicate findings (ideally, with different subject populations and different measures). ! ○ Overall, if a result replicates while using random assignment and manipulating IVs, we’re comfortable making claims about causality. ! ○ Causal logic is not a black-and-white “yes/no” decision. ● Or, it shouldn’t be.
  48. 48. OTHER TYPES OF RESEARCH ! ○ Observational research ● Researchers observe & take notes about people doing stuff. ● Do more kids hit each other on Playground A or B? ! ○ Archival research ● Analyzing behaviors that are documented in records. ● Do Republican and Democratic presidential candidates talk about different overall themes in their convention speeches? ! ○ Survey research ● Asking questions through a survey or interview. ● How happy are you? How often do you brush your teeth?
  49. 49. OTHER TYPES OF RESEARCH ! ○ Observational, Archival, and Survey research designs are usually correlational. ! ○ Correlational designs often used as a “first step” before an experimental design because they are easier & cheaper. ! ○ When are they not? ● If you manipulate something and participants are randomly assigned to receive different manipulations! ● Example: Half of your participants get your survey on green paper, and the other half get it on pink paper.
  50. 50. SOME OTHER USEFUL CONCEPTS FOR UNDERSTANDING RESEARCH
  51. 51. RELIABILITY & VALIDITY X Y ! ! x y ! ○ Example: Does self-esteem (X) lead to success (Y)? ! ○ Operationalizing ● We can use GPA or income (y) to represent success (Y) ● We can use a survey (x) to represent self-esteem (X)
  52. 52. RELIABILITY & VALIDITY ○ Validity ● Does the measure (x) accurately capture the variable (X)? ! ● Example: I.Q. tests (x) are one way to measure intelligence (X), but they may not capture everything important. ! ○ Reliability ● Does the measure (x) consistently give you the same assessment of the variable (X)? ! ● Example: If you take an I.Q. test four times over a year, will you get the same results (or pretty close) every time?
  53. 53. RELIABILITY & VALIDITY
  54. 54. RELIABILITY & VALIDITY ○ Weighing yourself on a scale... ● Let’s say you “really” weigh 150 pounds ● You weigh yourself every day for 1 week ! ○ Scale #1: Reliable but not valid ○ 120, 121, 119, 120, 120, 123, 117 ○ Consistent, but nowhere close to 150 ! ○ Scale #2: Valid but not reliable ○ 150, 140, 160, 145, 165, 130, 170 ○ Averages out to 150, but very inconsistent ! In both cases, you should probably buy a new scale.
  55. 55. RELIABILITY & VALIDITY ! ○ Example: Intelligence & IQ ! ! ○ If IQ is a reliable measure, we should get roughly the same IQ score every single time we take an IQ test. ! ○ If IQ is a valid measure, then it should correlate strongly & positively with your GPA, SAT/ACT scores, teacher evaluations, and scores on other intelligence tests, like the Cognitive Reflection Test.
  56. 56. RELIABILITY & VALIDITY ! ○ Example: What Is Love? Operational Definition: Palm Sweatiness & Heart Rate ! ○ If PSHR is a reliable measure, your amount of palm sweat and your heart rate should be roughly the same every time you look at your significant other. ! ○ If PSHR is a valid measure, it should be able to predict whether or not you’re still together in 6 weeks & how often you fight, and it should correlate with how much you say you love your significant other, how often you kiss/hug, how often you talk to each other, etc.
  57. 57. VALIDITY ○ Internal validity ● Did anything else except your IV affect the DV? ● Did we really measure what we wanted to measure? ! ○ External validity ● “Generalizability” ● Does it resemble real life and real situations? ● Could you get the same results again, even if you used... ○ Other operationalizations of the variables? ○ Other samples of people? ○ Other situations/contexts?
  58. 58. VALIDITY ! ○ Internal and external validity can be a trade-off. ! ! ○ The more closely your experiment resembles real-life and could be generalized to other people and situations (external validity), the more difficult it becomes to control all of the variables and isolate the one that you are truly interested in studying (internal validity).
  59. 59. APPLYING VALIDITY For this study, what are… The IV? The DV? Does this study have… Internal validity? External validity? Construct validity? Reliability?
  60. 60. APPLYING VALIDITY ○ IV: Drunkenness ● Operational Definition: Number of Drinks ○ DV: Motor Skills ● Operational Definition: Writing Ability ○ Internal validity: ● Can we be sure that the drinks are what caused the participants’ differences in motor skills? ○ External validity: ● Can we be sure that this would apply to other motor skills, other groups of people, other situations? Does this resemble the real-life problem? ○ Reliability: ● Would we get the same results if we did the test again?
  61. 61. FOR A QUIZ/TEST... ○ If you are given an experiment, you should be able to identify... ● Independent Variable(s) ● Dependent Variable(s) ● If it has validity ● If it has reliability
  62. 62. CHAPTER 2: 
 MOST IMPORTANT POINTS ○ Different types of research ! ! ○ Importance of Experiments ! ! ○ Experiment Components ○ Correlational vs. Experimental ! ! ○ Reliability & Validity ! ! ○ Random Assignment: What is it? Why is it important?

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