Research Methods in Psychology Strategies Statistics & Ethics.
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Transcript of Research Methods in Psychology Strategies Statistics & Ethics.
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Research Methods in Psychology
StrategiesStatistics& Ethics
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Research Strategies
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Research Strategies
• Experiment– Researcher changes one or more factors to observe
their effect on some behavior or mental process ⁺ DOES IDENTIFY CAUSE/EFFECT RELATIONSHIP⁻ Sampling errors, placebo effect, not natural environment
could alter true effect
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Research Strategies• Case Study (descriptive)
– in depth fact finding on a single subject⁺ Intensive, specific info⁻ No cause/effect; lots of time; no generalization
• Naturalistic Observation (descriptive)– Observation in natural/real setting without changing
environment⁺ Gathers naturally occurring data; real world⁻ Observer bias; no cause/effect
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Research Strategies
• Survey Research (descriptive)– Collect data through interviews questionnaires
• {but beware of:}– false consensus effect– bad sampling (especially self-selection!!!)
• Reduces validity and reliability = wording effects
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Research Strategies
• Correlational studies (descriptive)– Examines the degree* of relationship between
two variables⁺ Study real world connections⁻ NO cause/effect just CONNECTION– *”degree of relationship” just means how much they
correlate.
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Research Strategies
• One last note about correlational studies:
If you HAVE to get a tattoo, then I suggest the following:
“Correlation is not causation.”
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Research Strategies
• If marbles of two colors are mixed well in the large jar, the fastest way to know their ratio is to blindly transfer a few into a smaller one and count them
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Research Strategies
• Population– all the cases in a group, from which samples
may be drawn for a study
• Random Sample– a sample that fairly represents a population
because each member has an equal chance of inclusion
• Stratified random samples
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Experiments (cont…)
• Three Possible Cause-Effect Relationships(1)
Low self-esteemDepression
(2)Depression
Low self-esteem
Low self-esteem
Depression
(3)Distressing events
or biologicalpredisposition
could cause
could cause
could cause
or
or
and
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Controls
• Single & Double-blind Procedures– Subjects (or both the subjects and the research
staff )are ignorant (blind) about whether the subject has received the treatment or a placebo
– commonly used in drug-evaluation studies• Placebo
– an inert substance or condition that may be administered instead of a presumed active agent, such as a drug, to see if it triggers the effects believed to characterize the active agent
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Controls
• Random Assignment–assigning subjects to experimental and
control conditions by chance–minimizes pre-existing differences
between those assigned to the different groups
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Controls
• Experimental Condition– the condition of an experiment that exposes
subjects to the treatment, that is, to one version of the independent variable
• Control Condition– the condition of an experiment that contrasts with
the experimental treatment – serves as a comparison for evaluating the effect of
the treatment
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Controls
• Independent Variable – the hypothesized cause of a phenomenon– typically manipulated by experimenter
• Dependent Variable – the hypothesized effect in a phenomenon– in psychology it is usually a behavior or mental
process – measured by the experimenter
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Controls
• So how do you control for the big daddy of confounds, Chance?– Random assignment to conditions PLUS– Inferential statistics
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Research Strategies
Comparing Research MethodsResearch Method Basic Purpose How Conducted What is
Manipulated
Descriptive - To observe and Case studies, surveys, NothingOne variable at record behavior and naturalistica time observations
Descriptive - To detect naturally Computing correlations NothingTwo variables occuring relationship , sometimesat a time to assess how well among survey
one variable predicts responses
Experimental To explore cause Manipulating one or Independent and effect more factors and using variable(s)
random assignmentto eliminate preexistingdifferences among subjects
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Statistics
• Statistics come in two basic flavors:– Descriptive (duh.)– Inferential : did my observed result REALLY happen,
or was it just by chance?
Descriptive stats tell you 3 basic things:1.Central tendency2.Variability3.Correlation
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• Mode– the most frequently occurring score in a distribution
• Mean– the arithmetic average of a distribution– obtained by adding the scores and then dividing by the
number of scores• Median
– the middle score in a distribution– half the scores are above it and half are below it
Mathematical Tools-- Central Tendency --
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• Range– the difference between the highest and lowest scores
in a distribution• Standard Deviation
– a computed measure of how much scores vary around the mean
• Statistical Significance– a statistical statement of how likely it is that an
obtained result occurred by chance
Mathematical Tools-- Variation --
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Mathematical Tools-- Covariation --
• Correlation Coefficient– a statistical measure of the extent to which two factors vary together and
thus how well either factor predicts the other
Correlation coefficient
Indicates directionof relationship
(positive or negative)
Indicates strengthof relationship(0.00 to 1.00)
r = +.37
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Mathematical Tools
Height and Temperament of 20 Men
123456789
10
11121314151617181920
80636179746962757760
64767166737063716870
75666090604242608139
48697257637530578439
SubjectHeight in
Inches Temperament SubjectHeight in
Inches Temperament
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Mathematical Toolsaka Statistical Reasoning
• Scatterplot– a graphed cluster of dots, each of which represents
the values of two variables– the slope of the points suggests the direction of the
relationship– the amount of scatter suggests the strength of the
correlation• little scatter indicates high correlation
– also called a scattergram or scatter diagram
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Mathematical Tools
• Scatterplot of Height and Temperament
55 60 65 70 75 80 85
959085807570656055504540353025
Temperamentscores
Height in inches
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Mathematical Tools
Perfect positivecorrelation (+1.00)
No relationship (0.00) Perfect negativecorrelation (-1.00)
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Mathematical Tools:Inferential statistics
• SOLE purpose: is this result due to chance or not?– Typically assessed with a “probability value” or “p-
value”– Cut off is usually .05 (but there’s nothing magical
about that number!)– P-values are NOT measures of “effect size”– Effect size is always more important.
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Statistical traps…
• Mistaking correlation for causation– the perception of a relationship where none exists– (re: availability)
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Statistical traps…Random Sequences
• Your chances of being dealt either of these hands is precisely the same: 1 in 2,598,960.
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Statistical traps…Cheating with graphs:
Our Brand Brand BrandBrand X Y Z
100%
99
98
97
96
95
Percentagestill functioningafter 10 years
Brand of truck
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Statistical traps…Cheating with graphs
Our Brand Brand Brand Brand X Y Z
100%
90
80
70
60
50
40
30
20
10
0
Percentagestill functioningafter 10 years
Brand of truck
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Statistical traps…Which mean is which?
• A Skewed Distribution
15 20 25 30 35 40 45 50 90 475 710
70
Mode Median Mean
One Family Income per family in thousands of dollars
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World’s fastest ethics lecture
• Doing research with humans – basic principles:– Rights & well-being of participants outweigh the
benefits of the research
– Participants have to be allowed to decide to participate or not: Informed Consent is the cornerstone of ethical research.
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World’s fastest ethics lecture
– Participants have the right to withdraw from the study at any time, without penalty.
– Participants must be protected from risks or informed of risks that can’t be removed. Risk/benefit ratio must be positive.
– Deception is avoided whenever possible and must be justified if it is used.
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World’s fastest ethics lecture
– Researchers have the duty to inform the participants of the true purpose of the study (usually done in the debriefing)
– Data must remain confidential and secure (trickier these days with computers!)