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38 Cards in this Set
- Front
- Back
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what are the three different methodologies?
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true, quasi, correlational
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what are the three design considerations
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sampling, controlling extraneous variables, within subjects design vs. between subjects
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two types of sampling
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probability sampling and non probability sampling
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three types of extraneous variables
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confounding variable, experimenter bias, subject bias
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two types of probability sampling
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simple random sample, cluster sample
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two types of non probability sampling
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convenience sample, snowball sample
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what is effect size
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d=.2 small effect
d=.5 medium effect d=.8 large effect |
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what is explained variance
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% DV can be explained by IV
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assumptions of 2 independent samples t-test
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1.independent samples
2. normally distributed scores from pop 3. homogenity of variance (similar variance in each group |
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assumptions of 2 dependent samples t-test
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1. dependent scores as pairs, but independent for each set of pairs
2. normally disputed D scores from pop |
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two types of estimation
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point estimates, confidence intervals
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what is point estimates
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computed stats that estimate a parameter e.g. M is a point estimate for u. s is a point estimate for sigma
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what test do u use for 2 independent samples
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unpaired t-test
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what test do u use for 2 dependent samples
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paired t-test
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what test do u sue for 3 or more sample between subjects
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one way anova
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what test do u use for 3 or more sample withing subjects
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one way anova repeated measures
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assumptions of 3 between subjects anova test
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1. independent observations
2. normally distributed scores from pop 3. homogeneity of variance |
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assumptions for 3 within subjects anova test
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1. dependent scores for related conditions but independent for each set of conditions
2. normally distributed scores from pop 3. homogeneity of variance |
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what is a main effect
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the effect of one IV alone
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what is an interaction
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the effect of one IV at all levels of the other IV
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assumptions for 2 way anova
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1. independent observations
2. normally distributed scores from pop 3. homogeneity of variance |
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what is true experiment
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randomly assign to groups
infer causalty |
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what is quasi experiment
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cant randomly assign to group
cant infer causality use when there is a subject variable or any within subject experiments |
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what is subject variable
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a characteristic of an individual e.g. gender, height
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what is correlational methods
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examines the relationship between 2 variables
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what is operational definitions
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the precise way that you define variables in your study
use what has been previouly used questionaire, intervies, games |
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what is probability sampling
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types of random samples
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what is non probability sampling
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types of non random samples
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does random sample mean true experiment
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no
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what is a confounding variable
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a variable that varies along IV e.g. letter M and Q
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how to minimize confounding variables
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eliminate it, make it an IV, match subjects
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what is extraneous variable
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interferes with your ability to draw valid conclusions
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what is experimental bias
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experimenter's expectations could influence the outcome
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how to minimize experimental bias
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use double blind study, make conditions as similar as possible
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what is a subject bias
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tendency for subjects to behave in ways different from their normal behavior
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how to minimize subject bias
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use single blind study, dont use self report, use deception, make conditions similar
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what are the advantages of within subject test
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1. treatment group is its own control group
2. fewer subjects needed 3. can test sequences of development |
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what are the disadvantages of within subject test
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1. lose subjects over time
2. order effects (fatigue, practice effects) |
