W8

Question 1

Advantages of experiments

Answer 1

• allow to determine which variables have an authentically causal design
• identify variables that have significant causal relationships
• identify variables that have no significant effect on other variable

Question 2

Disadvantages of experiments

Answer 2

• artificiality of experimental conditions (lab setting - not real life scenario) –> lack of ecological isomorphism
• more sophisticated designs may require large number of people who are willing to become experimental participants, maybe for extended periods of time

Question 3

Lack of ecological isomorphism

Answer 3

conditions in lab as not the same as the ones in the outside world, meaning the study is not as replicable

Question 4

Ex-post facto designs

Answer 4

no manipulation of the IV, but still the relationship between variables and potential causes are studied

research analyzes the effects of an IV that has occurred naturally (e.g. gender, level of education) on a DV (e.g. academic performance, communication style)

Question 5

Field experiments

Answer 5

expose participants to different conditions to compare the effects of the manipulation on the IV (diff conditions)
e.g.
condition 1: studying in a group
condition 2: studying individually
observation: test performance

Question 6

Ex-post facto vs field experiments

Answer 6

ex-post facto designs and field experiments may not be as reliable as the researcher has no idea how individuals in the two groups differ outside of the conditions they were assigned to

it may be that some other circumstance other than their condition explains the difference in results.

Question 7

Basic experimental design

Answer 7

x= manipulation of variable (conditions)
r = random assignment of individuals to groups
O1 O2 etc = observation 1, observation 2, etc.

Question 8

One group pretest-posttest design

Answer 8

O1 X O2
to be certain that a causal relationship is found rule out two possibilities:

1) O2 may have occurred anyway for some reason (snot necessarily due to O1)
2) some influence other than the study conditions caused the change

rule out all other possible explanations before deciding that only the study conditions are explaining the difference in the observations

Question 9

Designing for control

Answer 9

CV - not exposed to any change
control - remove all possible variables from experimental design to ensure only the IV is causing the changes

Question 10

Two group pretest-posttest design

Answer 10

O1 X O2
O1. O2

both groups are measured before and after one group experiences an experimental condition, the other group is the control group

Question 11

Designing for random assignment

Answer 11

allows to assume the probability of something occurring in one group is no greater or less than the probability of it occurring in another group

Question 12

Random assignment for 2 group pretest-posttest design

Answer 12

R O1 X O2
R O1. O2

Question 13

Solomon four-group design

Answer 13

1) compare pretest with posttest
2) compare control groups with experimental groups
3) also takes a look at a group to which nothing has happened except for a final test

Question 14

Factorial designs

Answer 14

analysis that examine the relationship among 3 or more variables - multivariate analysis
experimental designs that manipulate two or more variables - factorial designs

Question 15

Between subjects design

Answer 15

diff groups of participants are exposed to different conditions or levels of the IV, each participant experiences only one condition

Question 16

Within subjects design

Answer 16

same participants are exposed to all conditions of the IV, every participant experiences every level or treatment

Question 17

Time series analysis

Answer 17

when we cannot know if the results obtained at the end of the experiment will still be true at some point in the future, problem

Question 18

Internal validity - spurious relationship

Answer 18

not a genuine relationship between two variables but one that only seems to exist

Question 19

Threats to internal validity - selection bias

Answer 19

occurs when the sample used in the study is not representative of the population being studied

Question 20

Threats to internal validity - attrition

Answer 20

participants get overstimulated from the study and decide to drop out - boredom

Question 21

Threats to internal validity - repeated testing

Answer 21

participants become due to repetitions, more and more familiar with the study and might develop certain expectations on what is it about or the aim of the study

Question 22

Threats to internal validity - maturation

Answer 22

people change over time and if there is a long period of time between experiments the results may become susceptible to maturation.

Question 23

Threats to internal validity - diffusion

Answer 23

when the condition slightly spreads into the control group making the whole experiment less reliable

Question 24

Threats to external validity - ecological isomorphism

Answer 24

conditions in the lab are not the same as conditions in the real world

Question 25

Threats to external validity - hawthorne effect

Answer 25

when participants change their behavior because they know they are being observed

Question 26

Internal validity

Answer 26

is the effect you find actually caused by your independent variable or by something else? the certainty with which you can find causal relationships in your research e.g. adolescents feel lonely the more often they use instagram (make sure loneliness is only being caused by instagram)

Question 27

Causality principals (internal validity)

Answer 27

1) co variance - y must change as x changes 2) chronology - x must occur before y 3) non spuriousness - nothing except x must be influencing y if you can control the circumstances in which the participants are being researched, you can rule out alternative explanations - make sure no other factors are affecting your results = high internal validity

Question 28

External validity

Answer 28

Extent to which results can be generalized to a context outside than the study itself To what extent do the results of your research say something about the population you are interested in? - we need a sample and circumstances for our research to allow us to make general statements

Question 29

Population validity (external)

Answer 29

results generalized to population to which you want to make statements for high population validity, do not exclude any groups from your population e.g. freq of exposure to election campaign - intention to vote sample: high educated students validity: low (bc sample does not represent the entire population)

Question 30

Ecological validity (external )

Answer 30

results generalized to real conditions / different circumstances research and results should represent "real life" situation, be as real as possible

Question 31

True experiments

Answer 31

experimental designs - maximize internal validity (aka randomized control trials / true experiments) manipulation: cause -> effect, cause is manipulated by researcher to have an effect comparison: cause -> effect, ensures effect does not occur naturally random assignment: random assignment of population into different groups, equal distribution, no systematic difference between the groups, if it fails replicate the study to ensure results are consistent

Question 32

Manipulation

Answer 32

control over the IV the level indicated by independent variable is determined by researcher control over external variables - rule out alternative explanations experimental variable: IV fully controlled by researcher individual difference variables: variables that cant be controlled by researcher (age, gender,etc. ) seemingly non manipulative variables that can be manipulated: e.g. self esteem manipulation check: important to perform in order to. make sure you are not giving away (spoiling) the purpose of the experiment control of variables of desinterest: ideally the only difference in the experiment is the IV (Ceteris paribus principle = ALL OTHER THINGS ARE EQUAL)

Question 33

randomization

Answer 33

eliminates all systematic differences between participants in different conditions

Question 34

Advantages of surveys

Answer 34

- respondents can answer large numbers of questions rapidly - efficient as large numbers of people can answer surveys rapidly - you can make generalizations to large populations with confidence

Question 35

Disadvantages of surveys

Answer 35

- question formats, limited response options such as yes or no - do not allow to asses causal relationships having to decide whether or not the responses you received are valid

Question 36

Cross sectional surveys

Answer 36

collects data from a population at a single point in time, it does not gather info about changes over time

Question 37

longitudinal studies

Answer 37

follow a subject/changes over time

Question 38

trend studies

Answer 38

measure the same variable over time using different samples from the population at each survey

Question 39

panel studies

Answer 39

group of individuals is recruited and surveyed over time

Question 40

cohort studies

Answer 40

track a specific group of people who share a common event

Question 41

cross lagged surveys

Answer 41

measure both dependent and independent variables at two different time, allowing researchers to infer causality

Question 42

probability sampling

Answer 42

simple random sample - every single person has the same chance of being selected from a population you can find possible biases within the simple random sample

Question 43

under coverage bias

Answer 43

not everyone in the population is included in the sample frame

Question 44

sampling bias

Answer 44

not every person in the sampling frame is equally likely to be included in the sample, if you fail to make a random sample

Question 45

non response bias

Answer 45

some respondents may not agree to participate or answer all questions

Question 46

response bias

Answer 46

maybe some respondents feel that some answers are socially unacceptable, hence, are not true to their responses