Critically Evaluating Research Part 1

Variables are

characteristic, trait, or condition that can take different values for different people

variables have

variance or variability

examples of variable

age, test score, fav. color

there are 2 types of variables

measured and manipulated variables

Measured variables are

variable that the researcher observes or records as it naturally occurs, rather than changing or assigning it

measured variable is also called

dependent variable

examples of measured variable

height, weight, hours of TV watched per week, gender identity, racial identity, intelligence, etc.

Manipulated variables are

variables that the researcher actively changes, assign, or control

manipulated variables are also called

independent variables

examples of manipulated variable

amount of coffee, drug dosage, conditions while performing the task (listen to music vs. silence)

you can find manipulated variables in both

experimental and quasi-experimental

conceptual variables are

the abstract concept you’re interested in studying

example of conceptual variable

intelligence, agreeableness, job satisfaction

Operation variables are

measurable way that “abstract concept” is defined in a study

examples of operational variable

to measure intelligence → IQ test score

to measure memory → number of word recalled

3 types of claims

Frequency, Association, and Causal

Claims in the case means

statement or conclusion the researcher is saying is true, “take home message”

Frequency Claim is

an estimate of the rate or levels of a single variable (how often does this happen)

examples of frequency claim

1) 30% of college students experience test anxiety

2) the avg. sleep duration is 6.5 hours

Frequency claim focus on producing

reliable estimate of a single variable and sometimes how much it varies

Large and representative samples are

key (in the thousands)

Association Claim is

saying that 2 things are related or covary/correlate, but not that one cause the other (whether the 2 variables move together or not)

correlation doesn’t mean

causation!!!!

example of association claim

1) Students who sleep more tend to have higher GPAs

2) Stress levels are associated with memory performance

Correlation: moving together

positive correlation (+,+) (-,-)

Correlation: one variable increases while the other decreases

negative correlation (+,-) (-,+)

Correlation: the 2 variables aren’t related in any way

No correlation

Causal claim is

differences in one variable are responsible for corresponding differences in another (cause & effect claim) [does one variable cause another?]

example of causal claim

1) Getting 8 hours of sleep improves exam performance

2) Caffeine increases reaction time speed

Causal claim is the type of claim you should be

most suspicious of and need evidence for (methods? how were constructed variables operationalized??)