lecture 5 Flashcards

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1
Q

operational definitions:

A

definitions of variables in terms of the operations needed to produce them

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2
Q

how to define operations?

A

replication by other researchers and scrutiny by other researchers

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3
Q

extraneous variables (confounders)

A

have an unintended influence on the results of experiment by changing difference between groups

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4
Q

when an extraneous variable is present. the experiment is:

A

confounded

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5
Q

nuisance variables:

A

unwanted variables that can cause the variability within all groups to increase

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6
Q

example of extraneous variable:

A

giving encouragement and warning to gaming participant

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7
Q

example of nuisance variables:

A

not holding ruler a precise distance above participants hands

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8
Q

how to control extraneous and nuisance variables:

A

produce groups that are equivalent prior to the intro of the IV. reduce the effects of nuisance variables as much as possible

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9
Q

randomization:

A

distributes extraneous variables equally to all groups. eg those who drink cola A regularly and those who regularly drink cola B

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10
Q

elimination:

A

completely remove the extraneous variable from the experiment. ex test and remove those who are loyal to cola A or cola B, only test those who are undecided so there are no biases

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11
Q

constancy:

A

keeps an extraneous variable constant. ex only test people who haven’t drank any of their fav cola that day

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12
Q

balancing:

A

ensures that all participants receive extraneous variable to the same extent. ex if one always prefers the first cola since they’re more thirsty

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13
Q

counterbalancing can control for:

A

sequence of order effects

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14
Q

lesson of M&M sampling:

A

sample size really does matter, there is power in. large numbers

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15
Q

we must have a sample that is:

A

representative of the population we are studying

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16
Q

a representative sample is most likely with a ____ sample, where each member of the population has an ___ ___ of being selected in sample

A

random; equal likelihood

17
Q

types of sampling: (3)

A
  1. random sampling without replacement
  2. random sampling with replacement
  3. stratified random sampling
18
Q

basic research strategies:

A

single strata, cross sectional, longitudinal

19
Q

single strata:

A

looking at a single thing of the population of interest, ex percentage of green peanut m&ms

20
Q

cross sectional:

A

comparing of two or more groups during the same limited time period. ex percentage of green peanut verses green plain m&ms

21
Q

longitudinal:

A

obtaining research from the same group of people over extended period of time

22
Q

stratified random sampling

A

the total population is divided into homogenous groups (strata) to complete the sampling process and sample is drawn from each strata

23
Q

random sampling without replacement:

A

a subset of the observations is selected randomly, and once an observation is selected it cannot be selected again.

24
Q

random sampling with replacement

A

a subset of the observations is selected randomly, and once an observation is selected and can be selected again.

25
Q

validity of tests and inventories include:

A

content validity, concurrent validity, criterion validity

26
Q

concurrent validity:

A

the results of a particular test or measurement correspond to those of a previously established measurement for the same construct

27
Q

criterion validity:

A

evaluates how accurately a test measures the outcome it was designed to measure

28
Q

reliability for tests and inventors includes:

A

test retest, split half

29
Q

pilot testing:

A

preliminary testing done in advance of the complete study

30
Q

types of surveys:

A

mail/email/web survey, personal interview, phone interview

31
Q

mail/email/web survey benefits and negatives

A

fast, can get large numbers of participants, return rate can be low

32
Q

personal interview benefits and negatives

A

slow, expensive, interviews bias

33
Q

phone interview benefits and negatives:

A

good compromise, ability to randomly sample before cell phones

34
Q

correlational studies:

A

looks at the relationship between two continues variable , positive, negative and zero

35
Q

ex posto facto studies:

A

“after the fact” use an independent variable that has already varied

36
Q

ex posto studies sometimes called:

A

subject variables eg, gender, SES, experiences are things you cannot or would not manipulate