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86 Cards in this Set
- Front
- Back
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Population
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consists of all members of a group
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Sample
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subset of a population
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Descriptive statistics
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summarizes the data collected from the sample participants in a study
*summary statistics:measures of central tendency &variability* |
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Inferential statistics
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allows you to draw conclusions about your data that can be applied to the broader population
bigger samples=more confidence language of 'probability' |
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Mean
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average
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Median
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score in the exact middle of a set of scores
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Median location
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place in the sequence of scores where the median will lie
*(N+1)/2 |
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Outlier
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scores that are far removed from other scores in a data set
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Mode
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score occuring the most frequently
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Range
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simplest and crudest measure of variability: difference between high scores and low scores
=high-low+1 |
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Standard deviation
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a measure of the average amount by which the scores in the sample distribution deviate from the mean score (typical distance)
*large is spread out *small is tight around the mean *SS=E(x-mean)^2 *=\\/(SS/N) **expresses variability in the same units as original** |
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Variance
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number calculated just prior to taking the square root of std dev. central feature of "analysis of variance"
*SS/N=popluation *SS/(n-1)=sample **corrects for tendency to underestimate for variability |
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Histogram
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graph that shows thenumber of times each score occurs or how often within a defined range
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Frequency distribution
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a table that records the number of times that each score occurs
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Normal curve
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a hypothetical distribution of what all the scores in a population would be like if everyone was tested
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Stem and leaf display
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often used when there is such a wide range of scores that a simple frequency distribution and histogram would be cumbersome
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Null hypothesis
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assumption that there is no difference in performance between the different conditions
*can only be rejected,not accepted |
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Alternative hypothesis
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outcome you are hoping to find
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Alpha (a) level
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the probability of obtaining your particular results are due to chance
*usually .05 *.01(drug testing) *.10 (pilot study) |
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Type I error
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Rejecting the null when it is true (Alpha)
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Type II error
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Fail to reject the null and there is a significant difference (you are wrong) ((Beta)
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Systematic variance
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the result of some identifiable factor that you have failed to control adequately
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Error variance
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nonsystematic variability due to individual differences in participants in the two groups
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File drawer effect
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findings that found no difference and were less likely to be published were stored away in one's files
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Effect size
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provides an estimate of the magnitude of the difference among sets of scores
*Cohen's D |
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Meta-analysis
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uses the effect size analyses to combine the results from several experiements that use the same variables with different operational definitions
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Confidence Interval
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range of values that is expected to include a population value a certain percentage of the time
*tells us that we can be 95% confident that the interval that has been calculated captures the population mean |
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Power
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the chance of reject the null when it is false (experimenter heaven) ((1-Beta))
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Experiment
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systematic research study in which the investigator directly varies some variable, holds all other factors constant, and observes the resultsof the systematic variation
*investigating the effect of X on Y. |
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Independent variable
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the factor of interest to the experimenter, the one being studied
*minimum of two levels (2 conditions) |
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Field experiment
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experiments that take place in the field
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Field research
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any research outside of the lab, including both experimental and nonexperimental methods
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Situational variable
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independent variable in which subjects encounter different enviromental circumstances
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Task variable
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independent variable in which participants are given different types of tasks to perform
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Instructional variable
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independent variable in which participants are given different sets of instructions about how to perform
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Experimental group
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group in which the treament is present
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Control group
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group in which treatment is withheld
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Extraneous variable
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variables that are not of interest to the researcher but which might influence the behavior being studied if they are not controlled properly
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Confound
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any uncontrolled extraneous variable that "covaries" with the independent variable and coule provide an alternative explanation of the results
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Dependent variable
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those behaviors that are the measured outcomes of experiments
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Ceiling effect
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average scores for the different groups in the study are so high that no difference can be determined: this happens when the dependent measure is so easy that everyone gets a high score
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Floor effect
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all the scores are extremely low because the task is too difficult for everyone
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Subject Variable
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a type of independent variable that is selected rather than manipulated by the experimenter; refers to an already existing attribute of the individuals chosen for the study
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Statistical conclusion validity
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concerns the extent to which the researcher uses statistics properly and draws the appropriate conclusions from the statistical analysis
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Construct validity
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refers to the adequacy of the operational definitions for both the independent and the dependent variables
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External validity
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the degree to which research findings generalize beyond the experiment
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Subject pool
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group of students asked to participate in research, typically as part of an introductory psychology course requirement
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Ecological validity
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Urlic Neisser: research with relevance for the everyday cognitive activities of people trying to adapt to their environment
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Internal validity
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the degree to which an experiment is methodologically sound and confound-free
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History
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when an event occurs between pre- and posttesting that produces large changes unrelated to the treatment program
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Maturation
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participants change from beginning to end of study
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Regression to the mean
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first score is high, next score will be closer to the mean
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Testing
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taking pretest influences posttest scores
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Instrumentation
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changes in the measurement instrument from pretest to postest
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Subject selection
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those participating cannot be randomly assigned to groups
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Attrition
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participants fail to complete a study; people finishing are not equivalent to those who started
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Between-subjects design
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any experimentaldesign in which different groups of participants serve in the different conditions of the study
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Within-subjects design
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any experimental design in which the same participants serve in each of the different conditions of the study
(repeated measures design) |
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Equivalent groups
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groups of participants in a between-subjects design that are essentially equal to each other in all ways except for the different levels of the independent variable
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Random assignment
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each individual volunteering for the study has an equal probability of being assigned to any one of the groups in the study
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Block randomization
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a procedure used to accomplish random assignment and ensure an equal number of participants in each condition; ensures that each condition of the study has a subject randomly assigned to it before any condition has a subject assigned to it again
*counterbalancing procedure used in within-subjects design* |
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Matching
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a procedure for creating equivalent groups in which participants are measured on some factor expected to correlate with the dependent variable; groups are then formed by taking participants who score at the same level on the matching variable and randomly assigning them to groups
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Matching variable
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any variable selected for matching participants in a matched groups study
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Repeated-measures design
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another name for within-subjects design
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Sequence (order) effect
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can occur in a within-subjects design when the experience of participating in one of the conditions of the study influences performance in subsequent conditions
*effect internal validity* *sensitization, progressive effect, carryover effect* |
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Progressive effect
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linear change in performance
practice: improvement across trials fatigue: decline in performance *regardless of particular sequence* (also sensitization) |
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Carryover effect
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non-linear, systematic change in performance across experimental conditions resulting from a particular
sequence |
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Counterbalancing
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for a w-s variable, any procedure designed to control for sequence effects
*always for w-s design *distribute sequence effects evenly across all conditions |
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complete counterbalancing
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every possible sequence of experimental conditions is used the same number of times
24 participants=4 conditions (24 sequences) |
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incomplete counterbalancing
(Latin Square) |
the most representative sequences of conditions are selected and used the same number of times
ABCD: ABDC BCAD CDBA DACB *only 4 conditions and not enough subjects for comp. cb. |
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randomized counterbalancing
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different orders are randomly selected from the set of available orders, and one order is randomly assigned to each participant
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reverse counterbalancing
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participants are tested more than once per condition; subjects experience one sequence, and the a second with the order reversed from the first
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Asymmetric transfer
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occurs when one sequence produces a transfer effect that is different from that produced by another counterbalanced sequence
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Cross-sectional study
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a design in which age is the independent variable and different groups of people are tested; each group is of a different age
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Longitudinal study
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a design in which age is the independent variable and the same group of people are tested repeatedly at different ages
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Cohort effect
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a group of people born at about the same time; cohort effects can reduce the internal validity of cross-sectional and longitudinal studies because differences between gruops could result from the effects of growing up in different historical eras
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Cohort sequential design
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a design that combines cross-sectional and longitudinal designs; a new cohort is added to the study every few years
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Experimenter bias
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occurs when an experimenter's expectations about a study affect its outcome
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Protocol
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a detailed description of the sequences of events in a research session; used by an experimenter to insure uniformity of treatment of research participants
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Double-Blind
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a control procedure designed to reduce bias; neither the participant nor the person conducting the experimental seeiions knows which condition of the study is being tested; often used in studies evaluating drug effects
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Participant Bias
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can occur when the behavior of participants is influenced by their beliefs about how they are supposed to behave in a study
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Hawthorne Effect
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name often given to a form of participant bias in which behavior is influened by the mere knowledge that the participant is in an experiment and is therefore of some importance to the experimenter
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Good subject Effect
Sensitization |
a form of participant bias in which participants try to guess the experimenter's hypothesis and then behave in such a way as to confirm it
performance later in study differs because hypothesis has been guessed |
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Demand Characteristics
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any feature of the experimental design or procedure that increases the chances that participants will detect the true purpose of the study
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Evaluation Apprehension
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a form of anxiety experienced by participants that leads them to behave so as to be evaluated positively by the experimenter
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Manipulation Check
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in debriefing, a procedure to determine if subjects were aware of a deception experiment's true purpose; also refers to any procedure that determines if systematic manipulations have inteded effect on participants
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