Experimental Psychology
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
Variables
independent variable—what the experiment manipulates; commonly the experimental and
control groups
dependent variable—what is being measured; should be measurable with numbers
Variables
confounding variables—variables that are unintended and throw off the experimental results
participant variables—relate to the subjects’ individual characteristics and can include
 personal background
 mood
 level of anxiety
 intellectual level
 awareness of the experiment
situational variables—relate to the experimental environment and can include
 room temperature
 noise
 distractions
 unplanned interruptions
Samples
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
matched pairs design—a design where subjects are matched on one variable, and then one
subject is given one condition of the independent variable and the other subject is given the
other condition (usually experimental and control conditions)
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
single participant/subject design—a design in which one subject’s performance over time or
across experimental conditions is tracked and recorded; this is not the same as a case study
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
Samples
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
opportunity sample—using an available, pre-existing group
Experimental Methods
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)
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
response bias—responding in a way the subject thinks the experimenter wants them to rather
than according to their own beliefs or cognitions; can be a result of demand characteristics; also
called the Hawthorne effect
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
Descriptive Statistics
descriptive statistics—statistics that are used to describe a set of data, including averages, most
frequent responses, the range of scores from high to low
levels of measurement
 nominal scale—a unit of measurement using named categories such as eye color, gender,
voting status, etc.; no logical order and no indication of how groups differ are apparent;
this is the least refined of the four measurement scales (e.g. Ford or Chevrolet, or Male
or Female)
 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. (e.g. good, better, best)
 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; there is no natural starting point at zero (e.g. temperature)
 ratio scale—a unit of measurement based on ordinal and interval scales but
comparisons can be made using ratios; saying a number is two or three times greater
than another number; this is the most refined of the four measurement scales; zero is
the natural starting point (e.g. age, weight, height)
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
 outliers—a value far away from the other values in a set of data
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
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
 frequency distribution—a summary of how often different scores appear within a set of
scores
 normal bell curve—a frequency curve in which most of the scores fall to the middle and
gradually taper off to the sides
Variables
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
response rate—in survey research, the percentage of responses returned from the sample
population
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
Inferential Statistics
inferential statistics—statistical score used to support an hypothesis and to make inferences about
the collected data
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
 in experimental research .05 is the accepted minimum level of confidence
 in other words, there is less than a 5% chance that are results are in error
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:
 Pearson product-moment (Pearson r) correlation coefficient shows the linear
relationship between two variables
 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
 dependent samples t-test is used for matched groups when a pretest and posttest have
been administered
non-parametric tests—tests in which the results do not fall into a normal distribution
 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
 chi-squared test—a statistical procedure for use with nominal (frequency counts) and
ordinal (percentages) data
Graphical Techniques
bar chart—a graph using bars to denote numerical counts
histogram—a bar chart that indicates the frequency of scores
line graph—a graph using lines to connect dots that denote numerical counts
frequency polygon—a line graph that indicates the frequency of scores
Ethical Considerations
there are six basic ethical considerations you need to address in any sort of research study:
informed consent--subjects should be told briefly what will be involved in the psychological
experiment.
 you do not necessarily need to explain your hypothesis but should explain what sort of
tasks will be required of the subject during experimentation
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
 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)
 some topics by their very nature may cause distress (e.g. cognitive dissonance or social
conformity)
 you must justify why the experimental design you have developed warrants these minor
discomforts
 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
right of withdrawal--at all times, subjects have a right to withdraw from the experiment
Ethical Considerations
anonymity—the assurance in testing the data results cannot be traced back to any individual
subject
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
 you cannot refer to subjects by name in your report
 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
participants are debriefed--all subjects should be debriefed at the conclusion of your experiment
 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
 you should briefly explain what theories support the behavior that they displayed in the
experiment
 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
Experimental Methods
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, also called the Hawthorne effect
 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)
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
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
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
advantages of observations include:
 lessening self-report bias and social desirability
 information is not limited to what the subject can recall
disadvantages include:
 difficulty in measuring complex behavior
 expense