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PSYC 3000

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  1. PSYC 3000

  2. PSYC 3000 C1-1 Know the five steps involved in the scientific method. “Know” means to be able to list and briefly describe each step (14-18). • ID problem: form hypothesis (a stated relationship between 2 or more variables) • Design experiment: control for extraneous variables • Conduct experiment • Analyze, interpret data • Communicate results

  3. Advantage of scientific approach… C1-2. What is the advantage that the scientific method offers over the other five non-scientific methods (19,3-20,0)? Objective observation: no personal bias/opinion

  4. Characteristics of science…. C1-3. List and describe, and give the relevance of each of the characteristics of the scientific approach (control, operational definition, replication). Be prepared to provide an operational definition of some concept that I might give you on the test (e.g., intelligence, anger). • Control: eliminating influence of extraneous variables • Operational define: terms and variables defined by steps or operations used to measure them • Replicate: data must be reliable/replicable *Operationally define “Intelligent”

  5. Operations Def… An operational definition of “Stupid” might be • Dumb • Unable to finish (no longer scrubbing) washing one’s hair within 5 minutes • Acts weird in public • Burps and acts like a wise-guy when sitting in a classroom • Doesn’t think well

  6. Four objectives of Science C1-4.Know the four objectives of science. On an exam, I might give you an example and request that you use the example to illustrate each of the objectives (26-29). • Describe: operationalize/define carefully • Explain: determine cause • Prediction: determine when event will occur • Control: produce event by manipulating antecedents (“make behavior happen”)

  7. Five Assumptions …. C1-5. Your author identifies five assumptions underlying science, starting with “Determinism”, with each point identified by a subheading. Be able to list and briefly describe each of these points (29-31). Determinism: causes of behavior and they are accessible (all behavior is caused) Reality in nature: events/objects in nature are real (vs. Plato: only real through perception) Rationality: events occur for logical reasons (can use reason to understand) Regularity: same laws of nature apply everywhere/all the time Discoverability: it’s possible to discover regularities and causes

  8. Why don't pigs drive cars?

  9. Why don't pigs drive cars? • They would become road hogs!

  10. Quiz! Reason is able to be used to help us understand the world, as the world operates in a logical manner. This is an example of: A. Determinism B. Reality in nature C. Rationality D. Regularity E. Discoverability

  11. Descriptive Research Approaches…. (chapter 2!) C2-1. Know the primary characteristic of the descriptive research approach (45,5) and for each of the descriptive research methods I cover in class. Be able to briefly describe what each is, and list the advantages and disadvantages (46-72). Descriptive Research Approach: observational, non-scientific • Accurately describes events/situations • No attempt @ discovering cause and effect relations Several methods (a sample): Secondary records: birth records, census, video recordings, etc. ADV: no reactivity DisADV: Selective Deposit—only some events recorded Selective Survival—only some records survive Example: Crack babies—reported in 1990s and beyond, but not available pre-1980s Naturalistic Study: observe naturally occurring behavior ADV: little reactivity; no artificiality DisADV: causes not discovered; time-consuming Example: Jane Goodall & chimpanzees; Diane Fossi & apes

  12. Descriptive Research Approaches…. Correlation Study: measure 2 or more variables & determine degree relationship between them. ADV: able to predict DisADV: third variable problem Example: SAT and GPA, Height & Weight Case Study: observe individual, event, or group ADV: intense observation of usually rare event DisADV: little control; can’t generalize; can’t ID causes Example: Freud’s methods Longitudinal Study: study individuals or some variable over a relatively long time period ADV: can see developmental changes over time DisADV: time consuming; no cause and effect; lose participants Example: follow set of students from childhood to adulthood (developmental psych.)

  13. Descriptive Research Approaches…. Cross-sectional: study different age individuals on some variable. Similar to longitudinal, but don’t follow over time—instead, get different aged participants. ADV: can examine developmental changes or skills at various age levels; less time-consuming DisADV: no cause and effect; cohort effect—different age groups may have been exposed to events that changed them (like 9/11 - a confound) Example: study participants aged 2, 4, 8, & 10 years Survey: snapshot of current attitudes, beliefs, etc. (“verbal reports”) ADV: may be predictive; some insight into current events DisADV: easily biased; people are poor observers of own behavior (inaccurate); positive self-presentation by participants Example: Gallup polls, Nielsen’s, etc.

  14. Descriptive Research Approaches…. C2-2 Know my point to be made in class regarding the survey as a verbal report versus direct observation of behavior. Also be able to recognize examples of and generate original examples of open-ended and close-ended survey questions. Be able to identify “double-barreled” questions as well as knowing the important points listed under the headings “ordering of the questions” and “questionnaire length” (65-66). Verbal Report is influenced by many things – language is easy to emit – often inaccurate. Comparisons of direct observation vs. verbal self reports reveal self report inaccurate! But… survey can give some preliminary information so…. • Ordering of questions: demographic questions first, because they are easy and “lead into” harder ones. • Short is better; in person is better (mail return is <2%). • Open-ended questions: Answer any way you want to. • Close-ended question: Limiting responses; easy to score. • Double-barreled: Two questions with only one response…how score?? • Biased: Slanted; leading to answer in a particular way.

  15. Population, Sample, & Random Sampling C2-3 Know the difference between the terms “population” and “sample” and know what “haphazard sampling” and “random sampling” are (67). Population: All people you are interested in Sample: a subset of the population you are interested in Haphazard Sampling: nonprobability; obtain participants where you find them. Could be a biased sample. Random Sampling: every member of population has an equal chance of being selected.

  16. Random Sampling 1 = Random sampling, 2 = Haphazard sampling You select every other person in the Turlock phone book for your study (your pop is all the folks in Turlock)

  17. Random Sampling 1 = Random sampling, 2 = Haphazard sampling You put all the names of everyone in the Turlock phone book into a hat, shake it up, then pull out 20 names that will be in your study.

  18. Random Sampling 1 = Random sampling, 2 = Haphazard sampling You put all the names of everyone in this class into a hat, shake it up, the take out 10 names who will be in your study. The class is your population of interest.

  19. The Experimental approach C 3-1 What occurs in an experiment? An experiment involves the independent variable being manipulated and others being controlled (the potential extraneous variables)

  20. Advantages of Experimental approach C 3-2 Know the advantages of the experimental approach—three are listed. Also know the disadvantages (also three listed) (87-89) Advantages of the experimental approach: * causal relationships can be stated with confidence * precisely manipulate one or more variables * usefulness—leads to solutions/more research Disadvantages * poor generalization from lab to “real” life * experiments are time consuming

  21. Field vs. Lab C3-3 Compare and contrast field experimentation and laboratory experimentation. What are the advantages and disadvantages of each? (92-95) Field Experiment Experiment conducted in real life setting (need manipulation) ADV: little artificiality (better generalization) DisADV: little control over extraneous variables (unsure of results due to IV or EX) Lab Experiment ADV: excellent control DisADV: Artificial (little generalization)

  22. Why do squirrels spend so much time in trees?

  23. Why do squirrels spend so much time in trees? • To get away from the nuts on the ground!

  24. Researchable or not? C4-1 Be sure to identify and generate examples of ideas that are and are not researchable (108) Researchable and non-researchable ideas • Researchable: (must be observable /measurable/ testable – empirical) b. Non-researchable: typically morality/religion/value judgment issues – non empirical!

  25. :45 0 of 35 A man’s soul weighs more than a woman’s soul • Researchable • Not researchable

  26. :45 0 of 35 The fastest way to Modesto is via the back roads (Santa Fe) versus 99. • Researchable • Not Researchable

  27. :45 0 of 35 Praying to God will reduce the length of a cold • Researchable • Not researchable

  28. :45 0 of 35 How long one can hold a 10 lb weight over their head • Not researchable • Researchable

  29. Why review the literature? C4-2. What are the benefits of reviewing the literature? (109) I found two points. • find out what’s been done b. point out methodological problems

  30. Criteria for research problem C4-3. Know the criteria in defining a research problem (“research question” is probably a better way to state this instead of conceptualizing all research as ‘problems’) and be able to generate examples or recognize examples of good and bad research questions (117-120). Criteria for the selection of a research question • states relation between 2 or more variables (often specifies direction of relationship) b. should be empirically testable

  31. Scientific vs. Null hypothesis C-4-4. Be able to clearly distinguish between a scientific hypothesis and a null hypothesis (120-122). Why is a null hypothesis tested and what is said when it is rejected? (122,0) Hypothesis: A statement specifying a relationship between 2 or more variables and is testable Scientific hypothesis: Predicted relationship among variables being investigated. Null hypothesis: A statement specifying no relationship among variables being investigated. IV has no effect of DV if null is correct. Reject the null = IV affected DV significantly

  32. :45 0 of 35 You state that caffeine will improve test scores • Scientific hypothesis • Null Hypothesis

  33. :45 0 of 35 You believe that caffeine will decrease test scores • Scientific hypothesis • Null Hypothesis

  34. :45 0 of 35 You state that you drinking watermelon juice prior to taking a test will not result in any change in one’s test scores. • Scientific hypothesis • Null Hypothesis

  35. All about ethics in research C5-1 Ethics in research • Milgram, Syphillis, huh? • APA code for ethical treatment • Types of stress: Physiological, psychological • Exempt vs. nonexempt • Informed consent • Some aspects: Confidentiality, special populations, right to withdraw, right to results, right to effective treatment, • Overriding principle, benefit outweigh cost

  36. IV and DV C6-1.Be able to define, recognize examples of and generate examples of variable, IV, DV, discrete variables, continuous variables, qualitative variables, and quantitative variables (191-193). Variable: measurable characteristic Independent Variable: Antecedent variable/manipulated Dependent Variable: Variable measured; detects influence of IV Qualitative Variable: Vary in kind Quantitative Variable: Vary in amount

  37. :45 0 of 35 The amount of caffeine in the bloodstream after drinking coffee is …. • Independent Variable • Dependent Variable • Factorial design • Anova • None of these

  38. :45 0 of 35 How fast one runs a mile after work is an example of • Independent Variable • Dependent Variable • Factorial design • Anova • None of these

  39. :45 0 of 35 How fast one hands out a test (slow or fast) • Independent Variable • Dependent Variable • Factorial design • Anova • None of these • Could be either

  40. IV and DV C6-2. Know the two requirements for a variable to qualify as an independent variable (194, 1). Be able to list and describe the three methods the author gives for manipulating variation (1194-197). Note that these categories are not independent of one another (lecture). IV must: be variable be able to be manipulated Three methods of manipulation: • presence/absence • amount of variable • type of variable

  41. IV and DV C6-3. Be prepared to recognize and generate examples of operationally defined IVs (205-207). Be able to give examples. Give an operational definition of an IV and a DV. E.g. provide an example of manipulating self esteem as and IV, or measuring self esteem as a DV.

  42. Construct Validity C6-4. Know the definition of "Construct Validity” and how it is established (2 methods listed in 209, 2-3). Also know the three methods for checking on the manipulation of the IV (210, 3-211,3). Construct: a consistent set of behaviors with a label on it, i.e., friendly, athletic, etc. Construct Validity of the IV (operationally defined): The extent to which an abstract construct can be inferred from the operational definition of that construct. Establish by… • Clear operational definition of abstract construct • Showing convergent (expected outcomes) and divergent data (diff measure and no relation to outcomes)

  43. Manipulating the IV C6-4. Know the definition of "Construct Validity” and how it is established (2 methods listed in 209, 2-3). Also know the three methods for checking on the manipulation of the IV (210, 3-211,3). Checking on manipulation of IV: Interview participants: to ensure that the IV had the desired effect on them. Behavioral Indicator (blood pressure/EEG/GSR) (or physiological indicators) Pretesting/pilot data

  44. More than one IV C6-4. What is the advantage of using more than one IV? Be able to define “Interaction” and give examples of it (212). Number of IVs: More than 1 gives interaction data (in addition to main effects) = Different effect a variable has on different levels of other variables Test scores Vitamins No vitamins Interaction Graph Make experiment only as complex as needed to show relationships clearly! factorial design (2X2; 2X4; etc.) Exercise No Exercise

  45. How many 9's are there between 1 and 100?

  46. How many 9's are there between 1 and 100? • 20

  47. DV C6-6.Know the definition of “DV”(213,1). What are the tasks of a DV (214,2-215,1). Your author lists three aspects of an experiment related to the DV that must be considered by the researcher. These include selecting the DV, the subject’s motivation level (“taking it seriously” p 215,1) and “cooperating” (215,1). DV: The behavioral variable designed to measure the effect of the variation of the independent variable. Dependent variable: should be: • Sensitive • Must ensure participant being serious and not “cooperative”

  48. Reliability and Validity C6-7. Know the difference between and the definition of reliability and validity. How are each established (217-221). Reliability of DV: Extent to which the dependent variable is consistent or stable over time. Measure must be reliable over time. Do replications and see if get similar measures on the DV Validity: The extent to which the DV measures what you want to measure Check by: Convergent data: extent to which similar measures correspond to measure used Divergent data: extent to which dissimilar measures do not correspond to measures used

  49. Disguising the DV C6-8. What are the benefits of disguising the DV (221,2)? (through distractions) • Participants take measure seriously • Participants’ demand characteristics controlled for

  50. Internal Validity C7-1. Know the definitions of internal validity and extraneous variable (229). What are the two methods of controlling extraneous variables (230-232). Know the point made in 232,2 regarding “The difficulty frequency lies in identifying those variables.” Internal Validity: Extent to which one can accurately state that the IV produced any observed effects on DV. Extraneous variables controlled by: • Elimination • Keep constant across groups/eliminate difference between groups (random assignment) You can’t identify all “participant variables” (possibly confounds such as gender, age, IQ, experience, etc.) . Can only control through random assignment (by balancing experimental and control groups)