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Agenda – Tuesday, January 14 th Psychologist Speed Dating Research terms – Research steps – Operational Definition Homework: Reading Guide #2 & Reading.

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Presentation on theme: "Agenda – Tuesday, January 14 th Psychologist Speed Dating Research terms – Research steps – Operational Definition Homework: Reading Guide #2 & Reading."— Presentation transcript:

1 Agenda – Tuesday, January 14 th Psychologist Speed Dating Research terms – Research steps – Operational Definition Homework: Reading Guide #2 & Reading quiz  WEDNESDAY

2 Speed Dating 1.) Introduce yourself 2.) Share your accomplishments and other information about yourself 3.) Explain your prop 4.) Listen for the question Be sure to take notes while listening to fellow psychologists!

3 Questions What influenced you to enter the field of Psychology? What are you most proud of from your career? If given the choice, what other psychologist(s) would you collaborate with?

4 Psychology = SCIENCE Relies on the Scientific Method – Coming up with a research question – Forming a hypothesis – Testing the hypothesis – Analyzing the results – Drawing a conclusion – Creating a theory

5 Psychology = SCIENCE Research relies on OPERATIONAL DEFINITIONS – A statement of procedures used to define research variables Examples – Right vs. left handed – When is homework “on time?” – Self-actualization

6 Agenda – Wednesday, January 15 th Research reading quiz Operational Definitions Finish basic research notes – Pseudoscience – Hindsight bias – Confirmation bias

7 Operational Definitions Memory improves with regular exercise People who use their phones in the car are unsafe drivers Participating in team sports builds character Tall people are more likely to be extroverts

8 Pseudoscience Claims presented as science, but without research adequate research to support it. To be science, something must be falsifiable (able to be disproven) Religious Explanations are not Falsifiable, and thus separate from Science.

9 Examples of Pseudoscience Holding Therapy for Attachment. Vaccines cause Autism. Telepathy exists. Sexual-Orientation Conversion Therapy Astrology (Events determined by placements of planets & stars) Freudian Thought (It used to be the best explanation)

10 Confirmation Bias Thinking welfare recipients are lazy & only noticing individuals that fit that belief. Accurately predicting the next song on the radio, but not remembering times you were wrong. Focusing only on vaccinated individuals who came down with Autism, while ignoring those without. Thinking violent video games cause violent acts & only noticing mass shooters who played them. Contributes to Overconfidence in our beliefs Causes Illusory Correlations

11 Michael Shermer (Skeptic Magazine)

12 Accepted Research must be… Both Reliable & Valid Study reporting a correlation between Mercury in Vaccines & Autism- Not replicable/Reliable Piaget’s research criticized for confusing tasks/questions- Not valid Reliablity: Hitting the same mark Consistently. Reliability does not ensure Validity!!!!!!!!!!!!! I understand the concept, but not this question?!?!?

13 White (84.3% = 386) Asian (1.9% = 9) Native American (10.6% = 49) Hispanic (1.6% = 7) Black (1.6% = 7)

14 White (57.4% = 263) Asian (20.6% = 94) Native American (8.4% = 38) Hispanic (5.8% = 27) Black (7.8% = 36)

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20 Scientists strive to minimize both error and bias in research. Error, as a technical term, refers to random variability in results. Some degree of error is inevitable in psychological research, as a researcher can never precisely control all the extraneous variables that can influence a measure of behavior. The occurrence of error does not imply that the researcher has made a mistake. Individual differences among the research subjects and imperfections in the measure of behavior, for example, contribute inevitably to error. Because error is random, its consequences tend to disappear when averages are calculated, especially when the data set is large. Researchers can measure error precisely, by calculating the standard deviation, and can take it into account in their inferential statistics. Therefore, error is not a devastating problem in research.

21 Case Studies Pros Cons Detailed analysis of a single or a few subjects (Ex. Freud’s Research) Phineas Gage

22 Case Studies Pros -Greater depth -Study things that would otherwise be impossible Cons -Individuals may be atypical -Can’t Generalize! Detailed analysis of a single or a few subjects (Ex. Freud’s Research) Visual Agnosia Phineas Gage Genie

23 Surveys gather information on personal characteristics Population (The ENTIRE group) Representative Sample (Larger=Better) Stratified Sampling (Race, Class, Gender Proportions) Random Selection (Everyone has = chance) Pros Cons

24 Surveys gather information on personal characteristics Population (The ENTIRE group) Representative Sample (Larger=Better) Stratified Sampling (Race, Class, Gender Proportions) Random Selection (Everyone has = chance) Pros - Can measure attitudes, motives, & opinions -Can get lots of data Cons -Wording Effect: Wording influences Answers. - Relies on honesty of participants. Ex. Social Desirability: Political Correctness. - Small response rate not representative.

25 Naturalistic Observation Observe behavior in a natural setting Can’t impact the behavior of participants! (Otherwise a Field Experiment) ProsCons Paul Ekman David Rosenham Participant Observation

26 Naturalistic Observation Observe behavior in a natural setting Can’t impact the behavior of participants! (Otherwise a Field Experiment) Pros -Results have real-world significance -Allows you to avoid ethical concerns. Cons -Only descriptive in nature -No control - Hawthorne Effect: Altering your behavior as result of being watched Paul Ekman David Rosenham Participant Observation

27 Correlational Studies Perfect Negative Correlation Perfect Positive Correlation Trying to establish a relationship between 2 variables. Helps Predict Behavior Corelation≠Causation (Ex. Shoe Size & Intelligence) Scatterplot 1 Shows a Negative Correlation As one variable ↓, the other ↑ Scatterplot 2 Shows a Positive Correlation Both Variables Move Together CC=-.63 CC=+.79 No Correlation Correlational Coeffecient: Shows Strength of Correlation -1--------------------0--------------------1 Regression Line Y’=a+bx Closer points=stronger correlation

28 Experiments Subjects should be randomly assigned to either group Control Group (No Ind. Var.) Dependent Variable Experimental Group (Indp. Var.) Dependent Variable Single-Blind: Subjects uninformed of group. Double-Blind: Researchers also uninformed. Limits Experimenter Bias Limits Participant Bias Can be given a placebo. Controls for psychological effects. The IV is what you expect to cause a change in the DV. Only way to establish Causation!!! Subjects selected (Random or Stratified) from Population. Con: Hawthorne Effect


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