PY3
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- Created by: Rosie Gibbs
- Created on: 15-01-13 11:45
differences found may be due to differences of participants
Participant Variables
1 of 42
data can be aranged in order but gaps between may not be equal
Ordinal Data
2 of 42
refers to practice, fatigue and boredom within repeated measures
Order Effects
3 of 42
Defining the variables so they can be precisley measured.
Operationalisation
4 of 42
predicts the main hypothesis is wrong and differences are due to chance
Null Hypothesis
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states the IV will have an effect on the DV but not the direction
Non Directional Hypothesis
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data that can be arranged in categories usually a bar chart
Nominal Data
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an independent measures design where participants in the second group are selected to match the 1st group
Matched Pairs
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behaviour and or expectations of the investigator influences results
Investigator effects
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a variable other than the IV that will effect the DV
Extraneous Variable
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checking results by asking someone else or an expert to look over what you did to obtain the information
Face/Content Design
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experimental design where seperate participants take part in each of the conditions
Independent Measures
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type of statistic that tries to infer info about a population using information gatherd by sampling
Inferential Statistic
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way of accessing reliability of recorded results to check correlate findings from all observers raters. if high correlation found then it is reliable.
Inter observer reliability
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a way of organising participants in an experiment
Experimental Design
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a general statment of what the researcher intends to find out
Aim
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type of external validity that can apply findings to another situation
Ecological Validity
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an hypothesis that states the IV will effect the DV
Directional
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value at which results from inferential test
Critical Value
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a way over over coming order effects (ABBA)
Counterbalancing
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statistic that shows strength and direction of a relationship
Correlation Coefficient
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indirect observation of material e.g.adverts, magazines
Content Analysis
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an EV that effects the DV but is not the IV
Confounding Variable
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name given to the main hypothesis
Alternative Hypothesis
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Value obtained after analysis of data using inferential test
Calculated Value
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variables that are involved in a correlation study
Covariables
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used in direct observations or content analysis to draw up a list of categories by which are used to count the frequency of that behaviour
Coding Frame
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units of behaviour that make up a coding frame to count frequecnies of specific behaviour
Coding Units
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comparing results to a recognised current measure or what you are testing, high positive correlation means you have...
Concurrent Validity
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a smaller scaled study to test out the materials that will be used
Pilot Study
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relates to whether findings apply to populations other than those studied
Population Validity
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having done one condition imporves another
Practice Effect
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participants are randomly assignes to an experimental group
Random Allocation
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every member of the poopulation has an equal chance of selection
Random Sampling
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consistiency either over time or within its self
Reliability
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where participants take part in each of the conditions
Repeated Measures
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probability results obtained were due to chance
Significance
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statistical test used for correlation with at least ordinal data
Spearmans rank
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way of checking inter rate relibility by spliting measure tool in 2 and compare participants results in both
Split Half
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to check external reliability by repeating experiment with same participant at another point in time
Test- Retest
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an hypothesis
Testable Statement
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truthfulness of a sttudy and whether it measures what it set out to measure
Validity
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Other cards in this set
Card 2
Front
data can be aranged in order but gaps between may not be equal
Back
Ordinal Data
Card 3
Front
refers to practice, fatigue and boredom within repeated measures
Back
Card 4
Front
Defining the variables so they can be precisley measured.
Back
Card 5
Front
predicts the main hypothesis is wrong and differences are due to chance
Back
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