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PSYC 3000
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PSYC 3000C1-1 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
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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
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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”
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Operations Def…
An operational definition of “Stupid” might be
1. Dumb
2. Unable to finish (no longer scrubbing) washing one’s hair within 5 minutes
3. Acts weird in public
4. Burps and acts like a wise-guy when sitting in a classroom
5. Doesn’t think well
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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”)
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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
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• Why don't pigs drive cars?
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• Why don't pigs drive cars?
• They would become road hogs!
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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
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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 reactivityDisADV:
Selective Deposit—only some events recordedSelective 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-consumingExample: Jane Goodall & chimpanzees; Diane Fossi & apes
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Descriptive Research Approaches….
Correlation Study: measure 2 or more variables & determine degree relationship between them.ADV: able to predictDisADV: third variable problem Example: SAT and GPA, Height & Weight
Case Study: observe individual, event, or groupADV: intense observation of usually rare eventDisADV: little control; can’t generalize; can’t ID causesExample: Freud’s methods
Longitudinal Study: study individuals or some variable over a relatively long time periodADV: can see developmental changes over timeDisADV: time consuming; no cause and effect; lose participantsExample: follow set of students from childhood to adulthood (developmental psych.)
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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 eventsDisADV: easily biased; people are poor observers of own behavior (inaccurate); positive self-presentation by participantsExample: Gallup polls, Nielsen’s, etc.
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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.
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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.
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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)
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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.
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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.
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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)
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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
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Field vs. Lab
C3-3 Compare and contrast field experimentation and laboratory experimentation. What are the advantages and disadvantages of each? (92-95)
Field ExperimentExperiment 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 ExperimentADV: excellent controlDisADV: Artificial (little generalization)
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• Why do squirrels spend so much time in trees?
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• Why do squirrels spend so much time in trees?
• To get away from the nuts on the ground!
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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 ideasa. Researchable: (must be observable /measurable/
testable – empirical)
b. Non-researchable: typically morality/religion/value judgment issues – non empirical!
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A man’s soul weighs more than a woman’s soul
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0%0%
1. Researchable
2. Not researchable
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The fastest way to Modesto is via the
back roads (Santa Fe) versus 99.
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0%0%
1. Researchable
2. Not Researchable
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Praying to God will reduce the length of a cold
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0%0%
1. Researchable
2. Not researchable
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How long one can hold a 10 lb weight over their head
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0%0%
1. Not researchable
2. Researchable
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Why review the literature?
C4-2. What are the benefits of reviewing the literature? (109) I found two points.
a. find out what’s been done
b. point out methodological problems
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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
a. states relation between 2 or more variables (often specifies direction of relationship)
b. should be empirically testable
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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
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You state that caffeine will improve test scores
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0%0%
1. Scientific hypothesis
2. Null Hypothesis
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You believe that caffeine will decrease test scores
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0%0%
1. Scientific hypothesis
2. Null Hypothesis
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You state that you drinking watermelon juice prior to taking a test will not result in
any change in one’s test scores.
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0%0%
1. Scientific hypothesis
2. Null Hypothesis
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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
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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
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The amount of caffeine in the bloodstream after drinking coffee is ….
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0% 0% 0%0%0%
1. Independent Variable
2. Dependent Variable
3. Factorial design
4. Anova
5. None of these
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How fast one runs a mile after work is an example of
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0% 0% 0%0%0%
1. Independent Variable
2. Dependent Variable
3. Factorial design
4. Anova
5. None of these
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How fast one hands out a test (slow or fast)
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0% 0% 0%0%0%0%
1. Independent Variable
2. Dependent Variable
3. Factorial design
4. Anova
5. None of these
6. Could be either
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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
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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.
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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)
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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
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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 vitaminsInteraction Graph
Make experiment only as complex as needed to show relationships clearly!
factorial design (2X2; 2X4; etc.)
Exercise
No Exercise
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• How many 9's are there between 1 and 100?
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• How many 9's are there between 1 and 100?
• 20
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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”
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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
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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
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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)
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Extraneous variables
C7-2. Be able to list and define the six extraneous variables that Christensen notes need to be controlled for. Be able to give an example of each and to recognize examples of each (233-240). (Most relate to pre-post-test design)
History—something which occurs between a pre & post test and may effect DV
Maturation—biological/psychological changes that occur with time passage
Instrumentation—assessment tool/person changes during course of study. Change in DV may be due to this. (combat with interobserver agreement)
Statistical Regression—high and low scores in a distribution will tend to regress back toward the mean (change in DV may be due to this) (usually happens with tests to raise very low scores) prevent: don’t use highs and lows, use a range. detect: use control group which should mimic stat. reg. (byproduct of poor selection)
Selection—when the selection of participants is NQR (not quite right) and the various groups are unequal in composition. Thus characteristics of participants may cause observed effect.
Mortality—unequal loss of participants from the various groups in the experiment (may account for difference between groups).
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Your research assistants start to like your research participant in a study designed to help folks to stop smoking. They gradually change their criteria to what is considered smoking from simply putting the cigarette in one’s mouth to actually breathing in smoke. This makes it look like the DV had decreases
when it has not. This is called:
450 of 35
0% 0% 0%0%0%0%
1. Statistical regression
2. Mortality problem
3. Maturation problem
4. History problem
5. Selection problem
6. Instrumentation problem
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You are measuring the effects of caffeine on people who experience panic attacks. One of your caffeine
groups is “run” over the fourth of July weekend. This could be an example of….
1. Statistical regression
2. Mortality problem
3. Maturation problem
4. History problem
5. Selection problem
6. Instrumentation problem
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Participant Effects
C7-3a. Be able to list and define the participant effects (demand characteristics, positive self-presentation) the experimenter effects (experimenter attributes, experimenter expectancies). In the section labeled experimenter expectancies, know the different effects on the experimenter and the participants (240-255)
Participant effectsA. Demand characteristics: cues which
give participant clues as to the nature of the experiment and they change their behavior.
B. Positive self-presentation: participants try to appear positive (and often use demand chars. in this quest!)
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kjfkjsdkfjksdjf
10%
90%1. Appropriate
2. Inappropriate
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Experimenter Effects
C7-3b. Be able to list and define the participant effects (demand characteristics, positive self-presentation) the experimenter effects (experimenter attributes, experimenter expectancies). In the section labeled experimenter expectancies, know the different effects on the experimenter and the participants (240-255)
• Experimenter effects:Attributes: the characteristics or skills of
experimenter may influence results. (gender, method of delivery, etc.)
Experimenter Expectancies: influence of the experimenter’s expectancies on outcomes.– Recording Bias– In interpreting data– Affect participants’ responses
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More Extraneous vars
C7-4. Know what a sequencing effect is, as well as subject sophistication (255-257).
More extraneous variables:
• Sequencing effect: prior treatment affects subsequent conditions
• Participant sophistication: being familiar with subject matter or with materials/procedure (more of a problem with repeated measures designs)
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Randomization
C8-1. Know what Randomization is, what it accomplishes (mention 'unknown sources of variation')(264), and how to do it (exhibit 8.1, page 266). What does "representative" mean? (267).
Randomization: The only known technique for controlling unknown sources of variation; every member of a population has an equal chance of being selected. (participant variables/extraneous variables)
Representative (Random selection): The extent to which a sample is similar in composition to a population.
Random Assignment should: Distribute potential extraneous variables equally to various groups.--by chance may get bias--the larger the sample, the less likely bias will occur
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Random Selection and Assignment
C8-2. What does Random Selection (sampling) assure, and what does Random Assignment Assure? (267,0)
Random Sampling (selection) assures a representative sample
Random Assignment assures a equal distribution of extraneous variables (participant variables) thus making your control and experiment groups equal in those potential confounding variables.
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More Extraneous vars
C8-3. Be able to define matching and know the two benefits (273-274,0)
Matching: equating groups on one or more variables by measuring participants on those variables and assigning them in equal amounts to the various groups.
ADV.increases sensitivity of experiment (the DV)More balanced groups
DisADV: time-consuming; pre-measuring induces demand characteristics
Precision Matching: each participant is matched to another on some variable.
ExampleStep 1: Measure on variable suspected of having impactStep 2: put in orderStep 3: Block according to number of groupsStep 4: RA participants from a block to one group – repeat this for each block.
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Matching
C8-4. Be able to define matching and know the two benefits (273-274,0)
Three groups – IV = Rock music, Classical music, no musicDV = performance on a math testMatching Variable: IQ scores
11210113211710412413611899113140106
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Controlling Subject Effects
C8-5. Know and be able to briefly describe the five general methods for controlling subjects effects (Double-blind placebo, deception, disguised experiment, independent measure of the dependent variable, and procedural/control of subject interpretation)(291-297)
Four General Methods for Controlling Subject Effects1) Double-Blind Placebo: Experimenter and participant unaware of
the conditions in effect (but aware they are in an experiment).2) Deception: Misdirect participants as to the nature of the
experiment. 3) Disguised Experiment: Participant is not aware they are
participating in an experiment.4) Independent Measures of the DV: Measure the DV away from the
experimental condition.5) Procedural control/control of participant interpretation – gain
insight into participants perceptions:A. Retrospective verbal report (exit interview)B. Concurrent Verbal Reports (think aloud)C. Sacrifice groups (terminate at various times)
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Control Recording Errors
C8-6. Know the various methods for control of recording errors:
Maintain observer awareness—continuous training
Multiple observers—inter-observer agreements
“Blind” data recorders—unaware of conditions in effect
Automation—computer/videos, etc.
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Control Recording Errors
C8-7. Be able to list, describe, or to apply any of the three "Control of Experimenter Expectancy Errors
1. Blind Technique – experimenter unaware of conditions (reduces bias)
2. Partial blind technique – keep experimenter “blind” as long as possible (reduces bias)
3. Automation – use computer, video tapes, audio recordings – minimizes errors
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A micro-switch in the base of little Johnny's chair allows us to detect if he gets off his seat. The experiment is investigating if caffeine
increases these out of seat episodes. The teacher is unaware if Johnny had caffeine or placebo. This is an example of…
20%
40%
0%
40%
0%
1. Automation
2. Blind technique
3. Multiple observers
4. Number 1 & 2
5. Nada!
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Faulty Designs
C9-1. Given a scenario which describes any of the faulty research designs, you should be able to point out the faults (e.g. potential confounds). There are three type of faulty experiments described (313-317)
A. 1-group after-only design: one group is measured on the DV after IV is manipulated/administered did a change in performance occur? For what reasons?
B. 1-group before-after design (pretest/posttest): change could be due to history/maturation/instrumentation/stat regression
C. Non-equivalent posttest only: could be differences between groups causing effects (ex. Joiners vs. nonjoiners) too small of a sample or not randomly assigned
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True Research Design
C9-2. Be able to list and describe the three
criterion that a true research design must meet:
A. Adequate answering of question/test of hypothesis (317,1)
B. Control of extraneous variables (318,1)C. Allows for generalizability/external validity
(319,3)
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True Research Design
C9-3. Know what a control and experimental group is, and the two functions that a control group serves (318,4-319,1)
Experimental group—receives some level of the IV
Control group receives no IV or some fixed/traditional levelControl group allows:
1. Comparison of scores with experimental group
2. “Control for rival hypotheses” meaning detect extraneous variable influences. (detect by looking at the changes…if DV changes also, then confound)
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True Research Design
C9-4. Be able to list and briefly describe the five reasons a pretest might be incorporated into a study. (320-322). Also know the two disadvantages of the pretest (322,3)
Pretest might be incorporated for:1) increased sensitivity/matching2) to determine if ceiling/ floor effect 3) get initial position/attitudes4) similar initial comparability: compare subjects5) evidence of change (after posttest) Disadvantages
ExpensiveDemand characteristics
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After Only Designs
C9-5. There are six "After-Only Designs" described in your text (323-341). Be able to describe each and list the advantages and disadvantages. Do the same for the Before-After Design described in 339-341.
1 Between groups/participants after-only design (diff. parts. in each group)
a. Control and experimental groupb. Random selection and random assignment
Disadvantage:Randomization could be biased (likelihood is a function of sample size)Not matched = less sensitive design
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After Only Designs
Simple Randomized Participants DesignA. Control and experimental groupB. Random selection and random
assignmentC. More than one level of the IV
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After Only Designs
Factorial Designa. Control and experimental groupb. Random selection and random assignmentc. More than one level of the IV and more than one
IV Can determine:
Main effect: the effect of each IV taken aloneInteraction effect: the effects one may have on DIFFERENT levels of another IV
Know: 2 x 22 x 3 x 22 x 4 x 6 x 2 (levels, # of variables, total number of
participants)
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A 2x2x5 factorial design has
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1. 1 IV
2. 20 Ivs
3. 3 Ivs
4. 9 IVs
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A 3 x 6 factorial design has
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1. 18 groups
2. 9 groups
3. 2 groups
4. 36 groups
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A 2 X 2 design could be
:400 of 35
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1. 0, 1, and 2 mg of caffeine and gender
2. Gender and room color: red, blue, green orange and white
3. Gender and a hot room or a cold room
4. Caffeine or not, and room color: blue, red, green.
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A 2 x 2 design, with 20 people per group, has
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0% 0% 0%0%0%
1. 24 participants
2. 80 participants
3. 40 participants
4. 100 participants
5. 20 participants
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After Only Designs
C9-6. In regard to a factorial design (328-335), know what a cell refers to; what the main effect and interaction effects are; and be able to recognize graphical displays of interaction effects (e.g. if they exist or not see figure 9.10)
Interpreting factorial design results1) If only main or only interaction effects, interpret both 2) If main and interaction effects: interpret only interaction
effects Problems with factorial:1) More factors = lots more participants2) Hard to manipulate more than 2 IVs3) Triple interactions and more = hard to interpretAdvantages of Factorial1) Test more (more IVs)2) Can build extraneous variables into experiment (like
gender…crowding…aggression levels)Can examine interactions (also more like real world)
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After Only Designs
4) Within-groups/participants after-only design (repeated measures)
all participants get all treatments
Advantages: don’t have to create equivalence on participant
variables fewer participants
Disadvantages: sequencing effects (who goes first/second) control with counterbalancing no control (detection) of history/maturation, etc.
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After Only Designs
Combining Between and Within Subject Designs(a factorial design)
More Variables studiedLess subjects than a pure between designCan test for interactions IV 1
IV 2
S1 S4
S2 S5
S3 S6
S1 S4
S2 S5
S3 S6
S7 S10
S8 S11
S9 S12
S7 S10
S8 S11
S9 S12
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Single Subject Designs
C11-1. Know what a single-SUBJECT design is in general (be able to describe its components) (373-377). Add to this that seldom is a single participant only used—usually 5-6 is used, providing replication evidence for any observed effects (lecture).
Examine one participant at a time to investigate the
effects of an IV (treatment).a. Repeated measuresb. “Baseline as a control and comparison”c. Use multiple participants = replications
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Single Subject Designs
C11-2. Be able to list and describe each of the single-participant designs listed (four are described). Know how each attempt to demonstrate that the independent variable was responsible for any effects observed (377-395).
ABA designBaseline (A) – Treatment (B) – Baseline (A)Withdrawal lends evidence that treatment caused effect!
ABAB designMore evidence!
Interaction Designs: Interaction refers to having two IVs
present at the same time thus:
A B A B A BC A B A……..
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Single Subject Designs
DV
Baseline - A Treatment - B Baseline - A
Be able to create an ABA, or ABAB graph
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Single Subject Designs
C11-2. Be able to list and describe each of the single-participant designs listed (four are described). Know how each attempt to demonstrate that the independent variable was responsible for any effects observed (377-395).
Multiple Baseline designs (across participants or situations/locations)
Baseline is recorded during the same time period for different lengths of time, for multiple participants. The treatment (IV) is introduced at different times for each participant (baseline is staggered/switch to IV is at different times for each participant to gauge the effect of IV)
No change in ongoing baseline is evidence that extraneous variables are NOT at work
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Single Subject Designs
C11-2. Be able to list and describe each of the single-participant designs listed (four are described). Know how each attempt to demonstrate that the independent variable was responsible for any effects observed (377-395).
Multiple Baseline designs
From: http://curry.edschool.virginia.edu/class/edlf/733/acts/mbline.html
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Single Subject Designs
Changing criterion designs
• If effects follow the change in the criterion (the IV) then evidence supports the IV causes effect in the DV.
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Single Subject Designs
Changing criterion designs
From:http://www.radford.edu/~pjackson/2SmallN.pdf
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Single Subject Designs
• Know the methodological considerations in using single-participant designs. Under the heading “Baseline,” I found four points regarding a stable baseline (absence of a trend; trend opposite to treatment effect; excessive variability; and reactivity). Know the critical issues related to changing one variable at a time (only change one!) (395,3-398).
• Stable baseline is characterized by:– Absence of trend and only slight degree of variability
(e.g. w/in 5% mean)– Trend opposite, treatment is powerful enough to
produce effect and reverse previous– Extreme fluctuations: check all components of the
study and try to identify and control sources of variability
– Reactivity: fact of using human participants—taking data itself may effect behavior
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Single Subject Designs
Knowing when to change from baseline to intervention:
1) Shouldn’t change baseline until observe:
Little variability
No trends
(but could if trend is opposite in direction to expected effect)
2) Only change one variable at time!
(Examples on board)
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Single Subject Designs
Knowing when to change from baseline to intervention:
1) Shouldn’t change baseline until observe:
Little variability
No trends
(but could if trend is opposite in direction to expected effect)
2) Only change one variable at time!
(Examples on board)
![Page 90: 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:](https://reader036.vdocuments.net/reader036/viewer/2022062421/56649d445503460f94a203fe/html5/thumbnails/90.jpg)
Scales of Measurement
S1-1. Scales of Measurement: important for selecting stat's (later on)
1. Nominal Scale: number is really a name!1 = male 2 = female
2. Ordinal Scale: number represents degree of an attribute: (order things!)take all exams and rank: 1,2,3,4,5,but 5-1 = 4 no information!
3. Interval Scale:A. different degrees of an attribute are indicatedB. different levels, or degree numbers are equally spacedC. zero point is arbitrary (doesn't indicate absence of variable)
4. Ratio Scale:A. numbers are equidistant (as in interval)B. numbers indicate diff. degree of attributeC. O indicates absence of attribute
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Which one is nominal?
450 of 5
1 2 3 4 5
20% 20% 20%20%20%1. The number of cigarettes a person
smokes in a day
2. Level in school: freshman= 1, sophomore=2, etc.
3. Age in years
4. How happy are you?
none 0 ------5 --------10 Lots
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Which one is ratio?
450 of 5
1 2 3 4 5
12% 12% 12% 12%12%12%12%12%1. Blood pressure level
2. Heart beat rate
3. Age in years
4. Number of dates one had last week
5. The number of hours of TV watched in a month
6. All of the above
7. None of the above
8. I haven’t the faintest!