Knowledge and RQs
Validity and Reliability
Research Designs
Participant Selection and Sampling
Statistics
100

Types of knowledge related to attributive, associative, and causal RQs

Descriptive, Predictive, Causal/Understanding

100

External validity is concerned with _______ while internal validity is concerned with ______.

Generalizability; Causal interpretation

100

To test a causal RQ we need to run a true experiment. What is required for a true experiment?

Random assignment, manipulation of the IV, and control of confounds

100

We want our sample to be _______ of the target population in order to ________ from our sample back to our target population.

Representative; generalize

100

Variable can be qualitative or quantitative. What is the difference?

Qual = categorical; different values represent different categories or groups

Quant = numerical; different values represent difference amounts

200

Source of knowledge that would state; "my mom says that kissing toads will give you warts!"

Authority

200

If we want to determine if the results of our study can be translated from the lab to the real world; what type of validity (specifically) are we worried about?

External validity; setting

200

The variable manipulated by the researcher, or the condition, or the level, or the causal variable is known as?

The IV (independent variable)

200

After 20 first years signed up for our study we changed our recruitment list to state third years only. What type of sampling technique is being used?

Stratified

200

Operationally define number of pets owned.

Ex: "do you have pets -- yes/no"

Ex: "how many pets do you have? ____"

Ex: "What types of pets do you own? dog, cat, bird, fish, etc."

300

Source of knowledge used in psychology

Scientific empiricism

300

Initial equivalence is maintained by?

Random assignment

300

Joe, Sally, Martha, and Pete complete the first level of the IV and then they complete the second level of the IV. Next their scores are compared. What type of design is this? Why?

Within-groups; because it is the same people in both conditions

300

We have a group of 100 participants. As the enter the lab, we send the first 25 to group 1, the second 25 to group 2, the third 25 to group 3, and the last 25 to group 4. What type of assignment is being used?

Arbitrary

300

Why do we care if our data is normally distributed? If we are interested in age of kindergartener and the mean is 5 with a SD of .5, are we worried that this might be skewed data?

All of our inferential statistics assume a normal distribution and do not function properly with non-normal data

+/-2SD check for skew leads us to 4-6 years old (probably ok)

400

RQs must have some way to collect data and be evaluated as well as be possibly wrong

Testable and falsifiable

400

Any variable other than ones controlled for or manipulated by the researcher.

Confound

400

Group 1 gets the standard treatment while group 2 gets the new treatment. Scores are compared at the end of the treatments. What is the causal (IV) variable? What is the effect (DV) variable?

Type of treatment; scores

400

What type of participant assignment is necessary for maintenance of initial equivalence and required for causal interpretation?

Random assignment

400

False alarm (when we say there is a significant effect in our data set but there is NOT a significant effect in the population) is also known as?

Type 1 error

500

Testing novel RQ, replication, and convergence

Three ways to apply the research loop

500

How consistent a measure is. 

Reliability

500

Why might be not be able to run a true experiment?

Not all IVs can be manipulated, may not be able to randomly assign, may have limitations due to ethics, tech, resources, etc.

500

What is the difference between the target population and a data sample?

Target pop = the people we want to study/generalize to

Data sample = participants from our study that provide us usable data

500

We are interested in evaluating the relationship between young adults and older adults on time spent of social media. What type of bivariate analysis is most appropriate?

t-test; age group (qual with 2 levels: young adults and older adults) and time spent on social media (quant: 0-15 million hours!)

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