PSYC206 Week TWO

Question 1

frequency claim aspects

Answer 1

1. focus on a single variable 2. use percentages, proportions, or averages 3. do not describe relationships or causes

Question 2

frequency claim example

Answer 2

60% of university students report high levels of stress

Question 3

association claims definition

Answer 3

describe a relationship between two variables

Question 4

frequency claims (definition)

Answer 4

describe how often something occurs or the proportion of people with a characteristic

Question 5

association claims aspects

Answer 5

1. involve two measured variables 2. use words such as associated with, related to, or linked to 3. do not imply causation

Question 6

association claims example

Answer 6

stress levels are related to sleep quality

Question 7

causal claims definition

Answer 7

state that one variable causes a change in another

Question 8

causal claims aspects

Answer 8

1. involve manipulated variables 2. use words such as causes, leads to, or improves 3. require stronger evidence than other claims

Question 9

causal claims example

Answer 9

increasing sleep duration improves memory performance

Question 10

what three criteria must be met for a causal claim to be justified?

Answer 10

1. covariance, the two variables must be related 2. temporal precedence, the cause must come before the effect in time 3. internal validity, there must be no plausible alternative explanations for the relationship

Question 11

how do experimental designs help meet the three criterias for justified causal claims?

Answer 11

1. manipulating the independent variable 2. controlling confounding variables 3. randomly assigning participants to conditions

Question 12

construct validity

Answer 12

how well the variables were operationalised and measured or manipulated

Question 13

external validity

Answer 13

how well the findings generalise to other populations, settings, and times

Question 14

statistical validity

Answer 14

how well the statistical evidence supports the conclusions (e.g., appropriate analyses, effect sizes, error rates)

Question 15

internal validity

Answer 15

how confidently we can conclude that one variable caused another

Question 16

frequency claims prioritise…

Answer 16

construct validity and external validity and focus on accurate measurement and representative samples

Question 17

association claims prioritise…

Answer 17

construct validity and statistical validity. focus on reliable measurement and strength of relationships

Question 18

causal claims prioritise…

Answer 18

internal validity. also require strong construct, statistical, and external validity

Question 19

lab experiments prioritise…

Answer 19

internal validity but may sacrifice external validity

Question 20

field studies may prioritise…

Answer 20

external validity but have less control over confounds

Question 21

surveys may prioritise…

Answer 21

construct validity and representativeness

Question 22

statistical thinking helps researchers:

Answer 22

1. describe patterns in data 2. make decisions under uncertainty 3. predict outcomes based on observed relationships

Question 23

what is a frequency claim?

Answer 23

a claim that describes how often something occurs in a population and involves only one variable

Question 24

evidence for frequency claims

Answer 24

descriptive statistics, survey or observational data, random sampling (representativeness)

Question 25

association vs causal

Answer 25

association: two variable are related, causal: one variable causes change in another

Question 26

why association does not equal causation

Answer 26

1. no temporal precedence 2. no control of confounds 3. fails internal validity

Question 27

'children who read more tend to perform better at school

Answer 27

association claim

Question 28

three criteria for causation

Answer 28

covariance, temporal precendece, internal validity

Question 29

covariance

Answer 29

variables are related

Question 30

temporal precedence

Answer 30

cause comes first

Question 31

internal validity

Answer 31

no alternative explanations

Question 32

why is internal validity important

Answer 32

- ensures cause => effect relationship is real - rules out confounding variables

Question 33

how do experiements establish temporal precedence?

Answer 33

researcher mannipulate the independent variable first, then measure dependent variable

Question 34

why does random assignment matter

Answer 34

equalises groups, reduces confounds, improves internal validity

Question 35

why internal validity isnt major for frequency claims

Answer 35

only one variable and no cause-effect relationship

Question 36

'how did researchers get their sample?'

Answer 36

external validity

Question 37

how well was sensitivity measured?

Answer 37

construct validity

Question 38

validities for frequency claims

Answer 38

1. construct validity (accurate measurement) 2. external validity (representative sample)

Question 39

why prioritise internal over external validity

Answer 39

to ensure causal conclusions are accurate, better to be correct than generalisable

Question 40

statistical thinking +uncertainty

Answer 40

1. helps interpret data patterns 2. allows probabilistic conclusions

Question 41

why stats don't prove things

Answer 41

based on samples, not whole populations

Question 42

descriptive statistics + patterns

Answer 42

summarise data using means, percentages, distributions and helps identify trends and relationships