Chapter 3 - Interrogation Tools for Consumers of Research

Question 1

define a measured variable

Answer 1

a variable in a study whose levels (values( are observed and recorded

Question 2

define a manipulated variable

Answer 2

a variable researchers control, usually by assigning study participants to the different levels of that variable. some variables cannot be manipulated due to ethical reasons, examples being childhood trauma or race.

Question 3

define constructs/conceptual variables

Answer 3

a variable of interest, at an abstract level, defined as part of a formal statement of a psychological theory. cannot be directly observed so we need to operationalize them.

Question 4

define operational variables/operationalizations

Answer 4

the specific way in which a concept of interest is measured or manipulated as a variable in a study. a definition of a concept in terms of precisely described operations, measures, or procedures.

Question 5

define the frequency claim

Answer 5

a claim that describes a particular rate or degree of a single variable. (ex. is how frequent or common something is)

variable is always measured and not manipulated and only focuses on a single variable.

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Question 6

define association claim

Answer 6

a claim about two variables, in which the value of one variable is said to vary systemically with the value of another variable. Mostly found in correlational studies

variables are always measured and involve at least two variables.

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Question 7

define the difference between a positive and negative association with the association claim

Answer 7

positive: high levels of one go with high levels of another, and same for low (linking exercise to higher pay)

negative: high levels of one go with low levels of another (coffee drinking leading to less depression)

Question 8

define causal claims

Answer 8

a claim arguing that a specific change in one variables is responsible for influencing the value of another variable. one variable is manipulated, and one is measured and the rest is held constant (an experiment)

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Question 9

define a variable

Answer 9

it is anything that varies. it has multiple levels (values).

ex. education can be broken down into different levels such as university, high school, and college.

if examining only a single value of a variable, then it is considered a constant

Question 10

how do scatterplots work to describe a correlation?

Answer 10

they show the association between two quantitative variables.

they display form, direction and strength (close bounded) of the association.

Question 11

how to know the difference between a causal and correlational relationship?

Answer 11

causal: X changes first and then causes Y to change too
- leads, results, affects, boost, could increase

correlational: X and Y change together
- related, associated, linked, worse, likely

correlational and causal can not be linked together!

Question 12

define validity

Answer 12

the appropriateness of a conclusion or decision

Question 13

define construct validity

Answer 13

an indication of how well a variable was measured or manipulated in a study. researchers must make sure that variables are measured reliably ( to get similar scores of repeated testing) and that the different levels accurately represent difference.

Question 14

define generalizability

Answer 14

the extent to which subjects in a study represent the population; how well the setting repreesnet other settings or contexts

Question 15

define external validity

Answer 15

an indication of how well the results generalize to, individuals or contexts beside those in the study itself

Question 16

define statistical validity

Answer 16

the extent to which statistical conclusions derived from a study are accurate and reasonable. How well can the numbers support the claim?

Question 17

how do we go about evaluating statistical validity?

Answer 17

• start at the point estimate (single estimate of some population based on the data)
• find the precision of that estimate with confidence interval or the marine of error of the estimate
• improve the validity with multiple estimates

Question 18

define confidecnce interval

Answer 18

range to capture the population value for some point estimate

Question 19

define margin of error of the estimate

Answer 19

inferential statistic providing a range of values that has a high probability of containing true population value

Question 20

what are the type of validity used for frequency claims?

Answer 20

construct, external and statistical validity

Question 21

how do we interrogate an assocation claim with validity?

Answer 21

see how well the correlational study behind the claim supports construct, external and statistical validity

Question 22

using construct validity for association claims

Answer 22

want to look at how both variables are measured. the variables need to be studied well in order for the results to be reported and have more confidence in them.

Question 23

define internal validity

Answer 23

in a relationship between A and B, the extent to which A, rather than some other variables C, is responsible for changes in B. ruling out that there is no thrid variables causing changes to B

Question 24

what is the 3 criteria for causation?

Answer 24

covariance, temporal procedence and internal validity

Question 25

define covariance

Answer 25

the degree to which 2 variables go together. the proposed causal variable must vary systemically with changes in the proposed outcome variable.

Question 26

define temporal precedence

Answer 26

stating that the proposed causal variable comes first in time, before the proposed outcome variable. ie. cause and effect

Question 27

define independent and dependent varible

Answer 27

independent is the one that is getting manipulated (must have more than 1 level) , and dependent is the one that is being measured to see if there is a cause and effect.

Question 28

define random assignment

Answer 28

use of random method to assign participants into different experimental groups

Question 29

how is validity shown in frequency claims?

Answer 29

construct: how did the research define the construct, measure the variable
external: how can we generalize to large population, how was sample selected
statistical: how accurate, margin of error (bigger the less confidence)

Question 30

how is validity shown in association claims?

Answer 30

construct and external: same as frequency
statistical: how strong is the association, more scattered points means weaker association

Question 31

how is validity shown in causal claims?

Answer 31

construct: is manipulation appropraite, how well is the outcome of the measured
external: same as other claims
statistical: does it minimize errors, looking at the average more than comparing
internal: can you rule out other variables that might have caused a change in the measured other than the manipulated

Question 32

what validity do you prioritize for a frequency claim?

Answer 32

external, you want it to be able to generalize to a bigger population

Question 33

what validity do you prioritize for a causal claim?

Answer 33

internal validity, you want to make sure there is no confounding variables involved with the experiment t change the results