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Transcript
Unit 6: Experimental Psychology
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Terminology
laboratory experiments—conducted in the lab
field experiments—conducted in the real world
Variables
independent variable—what the experiment manipulates; commonly the experimental and
control groups
dependent variable—what is being measured; should be measurable with numbers
confounding variables—variables that are unintended and throw off the experimental results
operational definition of variables—when an independent variable is defined according to the
events used to produce it (e.g. what constitutes “low anxiety” or “high anxiety”); a measured
operational definition applies to dependent variables that are defined in operational terms
research (or experimental) hypothesis—a detailed explanation of a predicted relationship
between certain conditions or variables; this hypothesis is not subject to change
null hypothesis—a detailed statement indicating there is no relationship between certain
conditions or variables
Validity and Reliability
replication—sufficient detail in the procedure section to duplicate the experiment with the same
materials and instructions
reliability—the ability to produce consistent and stable scores or results
validity—the ability of a measuring instrument or experiment to measure what is intended
internal validity—controls prior influence, maturation processes and the order effect, but not the
subjects’ history with the task
threats to internal validity include:
– unplanned events
– differences between subjects
– statistical regression
– testing problems
– changes in a measuring instrument
– natural changes in subjects over time
– experimenter bias and misuse of statistical tests
external validity—controls the subjects’ history with the task but not the other aspects
threats to external validity include:
– poor selection of subjects
– limited characteristics of the subjects
– limited operational definitions
– multiple treatment interference
– subject awareness of the study
– too limited a setting for the experiment
– a limited time frame in obtaining results
Quantitative Research Methods
these methods are used by psychologists to test hypotheses under rigorous, controlled
conditions
experiments take place in the laboratory or in the field
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the aim is to establish a cause-and-effect relationship through descriptive and inferential
statistics
statistics allow the researcher to determine the level of significance (at least at the .05 level)
triangulation—a multi-method approach to the study of human behavior.
– data—collected over time, in different locations, from different persons or groups
– investigator—data collected from different investigators
– theories from different perspectives—for example, how the cause of obsessivecompulsive disorder based on the behavioral, psychodynamic or biological perspectives
– methodological—data collected from within-subject designs and between-subject
designs on different occasions
Samples
population—the total number of people or things from which to draw a sample
sample—a small group of people or things selected to represent the target population
random selection of participants and random assignment to groups—helps to increase the
validity of the results
random sampling—selecting a sample from the population purely at random
representative sampling—occurs when the population is divided into subpopulations and then a
random sample is taken from each subpopulation
stratified sampling—a sample that matches the overall characteristics of the population from
which it is drawn
systematic sampling—a sample that is pulled from the population using a system or some
criteria, such as every 10th person
independent subjects design—a design in which groups of subjects experience different
experimental conditions; comparing a control group versus an experimental group is a common
independent samples design; measures two distinct groups
repeated measures design (within-subjects design)—a design in which one group is measured
before and then after administration of a variable; typically this involves a pretest and a posttest
Experimental Method
experimental group—a group that receives the experimental condition; the group that is affected
by the independent variable
control group—a group that does not receive the experimental condition; the group is not
affected by the independent variable
placebo group—a group that is a control group but receives a placebo to minimize subject bias (a
single blind experiment)
single-blind techniques—an experimental design in which subjects do not know which group they
are in, typically an experimental or control group; this reduces subject bias
double-blind techniques—an experimental design in which both the subjects and the
experimenter do not know which group is which; this reduces both subject and experimenter
bias
research bias and expectancy (researcher and participant effects)—bias that occurs
demand characteristics—a cuing in process which insidiously instructs subjects in an experiment
about what is expected (e.g. compassionate behavior, aggressive behavior, etc); if deception is
used as to the purpose of the experiment, such subject bias arising out of demand should not
occur
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participant and researcher expectancies—based on the idea that what the researcher expects
will alter the subject’s performance; this is known as the Pygmalion effect; this was shown by
Rosenthal’s study that experimenter expectancies can alter the performance of children in a
classroom (our 40 Studies article “What You Expect Is What You Get”; this highlights the need to
control experimenter bias
Questionnaires/Surveys
large-scale and small-scale surveys—the scale of the survey is dependent on the number of
surveys collected, either a lot (large scale) or a few from a select group (small scale)
use of Likert scale—a rating scale developed by R. Likert where respondents are asked to indicate
where they fall along some dimension
– this is then converted into a numerical score (e.g. strongly agree-1, agree-2, neither
agree nor disagree-3, disagree-4, strongly disagree-5)
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advantages include:
– flexibility in asking questions
– less time to collect data
– large amounts of data can be collected at once
disadvantages include:
– question-bias
– self-report bias
– erroneous memories of the subjects
– social desirability bias
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Naturalistic Observation
participant observation—the observer is part of the group being observed
non-participant observation—the observer remains detached from the group; sometimes called
a complete observer
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methods of recording data, including time, event and point sampling:
– duration recording—the observer specifies the length of time a particular behavior will
last (e.g. talking to other student; being out of one’s set)
– frequency-county method—counting the number of time (frequency) the behavior
occurs
– interval recording—a single subject is observed for a set amount of time and the
subject’s behavior is recorded
– continuous observation—after observing the subject, the observer gives a narrative
account of the observed behavior; it is up to the observer to determine which
behaviors are important to report
– time sampling—the observer randomly selects time period to observe the subject; this
is used in conjunction with duration recording, the frequency-count method,
interval recording and continuous observation
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advantages of observations include:
– lessening self-report bias and social desirability
– information is not limited to what the subject can recall
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disadvantages include:
– difficulty in measuring complex behavior
– expense
Descriptive Statistics
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levels of measurement
– nominal scale—a unit of measurement using named categories such as eye color,
gender, voting status, etc.; no order and no indication of how groups differ are
apparent; this is the least refined of the four measurement scales
– ordinal scale—a unit of measurement in which values to a variable can be rank ordered
from highest to lowest, such as class rank, percentile ranks, ordering ideas from best to
worst, etc.
– interval scale—a unit of measurement similar to ordinal scales but in which the
difference between each unit is equal or constant; the difference between 5 and 6 is the
same as between 17 and 18
– ratio scale—a unit of measurement based on ordinal and interval scales but
comparisons can be made using ratios; saying a number to two or three times greater
than another number; this is the most refined of the four measurement scales
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measures of central tendency
– mean—the average score from a group of scores
– mode—the most frequent scores that occurs in a group of scores
– median—the middle scores in a group of scores that separates the top half from the
bottom half from rank-ordered scores
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measures of dispersion
– range—the difference between the highest and lowest score
– standard deviation—a numerical index that tells, on average, how far the scores fall
from the mean; the larger the standard deviation, the greater the spread of scores
– variance—the second moment around the mean; the expected value of the square of
the deviations of a random variable from its mean value
– quartile and semi-interquartile range—divides ranked data into four parts or quartiles
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normal distribution of data
– standard scores—scores converted from raw score distributions; the two most common
are z-scores and T-scores
– frequency—the number of raw scores that fall within a class of scores
– skewed distribution—a distribution of scores that is not a normal distribution buy
extends more to one side or the other
 if the scores are skewed to the left (negatively skewed) the mean and median
are to the left of the mode
 if the scores are skewed to the right (positively skewed) the mean and median
are to the right of the mode
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Inferential Statistics
probability—an estimation of how many times a certain event is likely to happen
levels of confidence—the level of certainty that an inferential statistic is not due to chance
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in experimental research .05 is the accepted minimum level of confidence
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in other words, there is less than a 5% chance that are results are in error
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the appropriate choice of statistical tests and limitations upon their use
most of these tests are used to measure the relationship between two sets of scores:
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independent samples t-test is used for independent groups to determine if the mean on
one group is different from the mean of the other group to support a predicted
direction in an hypothesis
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dependent samples t-test is used for matched groups when a pretest and posttest have
been administered
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non-parametric tests—tests in which the results do not fall into a normal distribution
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Mann-Whitney U test—a test for use with two independent samples; the basis of this
test is that if all the data from the two samples are ranked, the high and low ranks
should be evenly distributed if the samples are equal
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chi-squared test—a statistical procedure for use with nominal (frequency counts) and
ordinal (percentages) data
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Graphical Techniques
bar chart—a graph using bars to denote numerical counts
histogram—a bar chart that indicates the frequency of scores
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line graph—a graph using lines to connect dots that denote numerical counts
frequency polygon—a line graph that indicates the frequency of scores
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Ethical Considerations
there are four basic ethical considerations you need to address in any sort of research study:
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informed consent--subjects should be told briefly what will be involved in the psychological
experiment.
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you do not necessarily need to explain your hypothesis but should explain what sort of
tasks will be required of the subject during experimentation
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justification for any discomfort or deception--you need to justify why you would cause a subject
any physical or mental discomfort, or deceive them in some way
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some experiments by their very nature may cause some mental frustration that would
be encountered day-to-date (e.g. challenging math or verbal problems, or making
choices between possible selections)
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some topics by their very nature may cause distress (e.g. cognitive dissonance or social
conformity)
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you must justify why the experimental design you have developed warrants these minor
discomforts
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Could this topic be tested any other way? Be sure to ensure accurate participation of
your subjects. Provide them with the appropriate environment in which to complete
their task. Be sure to conduct yourself professionally; the more professional and serious
you are, the better your results will be
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right of withdrawal--at all times, subjects have a right to withdraw from the experiment
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findings are confidential--while you can ask demographic information such as age, grade level,
sex, or GPA, you cannot record their names in connection with their results
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you cannot refer to subjects by name in your report
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you should make sure all data collected is done so anonymously and assure your
subjects that the results will only be used for this experiment and then discarded
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participants are debriefed--all subjects should be debriefed at the conclusion of your experiment
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you should explain to them at the time they participate, if possible, what you are testing
and how their results will be compared to others
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you should briefly explain what theories support the behavior that they displayed in the
experiment
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if debriefed at the conclusion of the experiment, you can share with them the results
and any conclusions you've made based on all the data you've collected
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Additional considerations for Psychology 1B experiments:
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you should always acknowledge the works and publications of others
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make sure you completely reference these sources both in your Introduction and in your
References sections
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be honest in reporting your results
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it is not important whether you prove your hypothesis but how well you conduct your
experimentation
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do not dry lab results (make up results without running an experiment) or skew your
results to support your hypothesis
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monitor that these ethical standards are being displayed by others in your group and in
the class
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the psychological research community is constantly vigilant in making sure these ethical
guidelines are adhered to
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in animal research, you must always justify any discomfort that the animal will
encounter