chapter 4

Question 1

generalizing

Answer 1

the process of making an inference that the results observed in a sample would hold in the population of interest

Question 2

generalizability

Answer 2

• the validity of such an inference or conclusion
• amount of truth in the conclusions drawn
• ability to apply what we have learned from our sample the the theoretical population we are interested in

Question 3

the sample

Answer 3

who is in your study

Question 4

sampling frame

Answer 4

how you get access to your sample

Question 5

theoretical population

Answer 5

to whom do you want to generalize too

Question 6

approaches to generalizability

Answer 6

• sample model
• proximal similarity model

Question 7

sample model - generalizable approach

Answer 7

• argues you draw a sample from the population and is either a good representations of the attitudes of the populations you are interested in or they are not
• either generalizable or not
• if its representative of the population you can generalize it

Question 8

proximal similarity model - generalizable approaches

Answer 8

• look at the sample and how closely similar it is the the group you want to generalize too
• how closely similar your sample is = generalizability

Question 9

sampling methods

Answer 9

• non-probability sampling
• probability sampling

Question 10

non-probability sampling

Answer 10

• sampling that does not involve random selection
• e.g. convenience, purposeful, modal instance, expert, quota, heterogeneity, snowball sampling methods

Question 11

convenience sampling (accidental sampling) - non-probability sampling

Answer 11

• a form of non-probability sampling
• choosing the sample based on how easy it is to find them
• using readily accessible groups
• easier/convenient
• limited generalizability
• e.g. convenience sample of intro psych. university students are VERY common

Question 12

purposeful sampling - non-probability sampling

Answer 12

sampling based on a specific set of criteria

Question 13

modal instance sampling - non-probability sampling

Answer 13

• typical (modal) case: depends on what we are trying to learn for e.g. looking at gamers changes based on age and game we are trying to focus on
• choose characteristics of typical case and select based on demographic statistics
• e.g. talk to a typical hunter about gun control

Question 14

quota sampling - non-probability sampling

Answer 14

• quotas we establish for our sample to match the general population
• create greater similarity between sample and population of interest
• proportional and non-proportional quota sampling

Question 15

proportional quota sampling

Answer 15

• match sample proportions to population on important variables
• e.g. if macewan student population is 70% women you want 70% of your study to be women

Question 16

non proportional quora sampling

Answer 16

• number quotas that are not proportional to the population
• e.g. using more then the percentage that exists in the population
• e.g. gender neutral bathrooms; using more than the general populations of trans individuals based on the fact it likely effects them more to compare their attitudes to non-trans individuals opinions

Question 17

snowball sampling - non-probability sampling

Answer 17

• used to reach inaccessible or hard to find groups for example when studying a furry; not all furries will want to be “outed” to the general public
• may end up with a narrow subset of the group you are interested in
• respondent driven sample: adds the use of mathematical modelling to compensate for the non-random nature of the sample and improves generalizability

Question 18

probability sampling procedures

Answer 18

• simple random sampling
• stratified random sampling
• systematic random sampling
• cluster/area random sampling
• multistage sampling

Question 19

simple random sampling - probability sampling

Answer 19

e.g. list of people that corresponds to the population and randomly draw names

Question 20

stratified random sampling - probability sampling

Answer 20

• the population is divided into subgroups (strata) based on shared characteristics
• then random samples are drawn from each stratum, ensuring each subgroup is adequately represented
• e.g. taking the list of names, dividing it into strata/subgroups and random sampling names form the strata

Question 21

systematic random sampling - probability sampling

Answer 21

random sampling using a system

Question 22

cluster/area random sampling - probability sampling

Answer 22

randomly sampling based on geographical area

Question 23

multistage sampling - probability sampling

Answer 23

• combining several techniques for greater efficiency and/or effectiveness
• more than one sampling strategy/a variety of methods

Question 24

internal validity

Answer 24

relates to the internal control that you exercise in a study and the ability to make a causal conclusion

Question 25

external validity

Answer 25

generalizability; is what is true in the sample also true in the theoretical population of interest?

Question 26

experimental designs

Answer 26

- independent variables (IVS) - dependent variables (DVS) - controlled variables

Question 27

independent variables (IVS)

Answer 27

- the variable that is manipulated - propordent cause - levels of the variable - e.g. no gum, mint gum, bubblegum; in a study on chewing gum

Question 28

dependent variables (DVS)

Answer 28

- depends on independent variables - can also have levels - propordent effect - predictor variable: cause - outcome variable: effects - e.g. test scores

Question 29

variables

Answer 29

- anything in your study that can vary - four categories: 1. situational variables 2. response variables 3. participant or subject variables 4. mediating variables

Question 30

situational variables

Answer 30

- anything you are exposed to in the research - e.g. room lighting

Question 31

response variables

Answer 31

- any response your subjects can give - something your subjects do for a purpose - explained by other factors - e.g. if your subjects do it, it's a response variable

Question 32

participants or subject variables

Answer 32

- variables that are innate parts of your subject that are either static or dynamic - vary from subject to subject - e.g. sex, height, weight, age, attitudes, beliefs

Question 33

mediating variables

Answer 33

- variable that mediates the relationship between other variables - researchers expansion for the relationship between other variables they are studying

Question 34

types of study

Answer 34

- descriptive study: attempt to describe what is, and what is wrong - relational study: examine the relationships between variables and differences between means - differences between means study

Question 35

correlations

Answer 35

- directionality problem: does x =y? or does y=x? - third variable problem: does z relate to x and y?

Question 36

positive correlation

Answer 36

higher scores on one variable are associated with higher scores on the other variable

Question 37

negative correlation

Answer 37

higher scores on one variable are associated with lower scores on a second variable

Question 38

questions

Answer 38

- broad statement idea for research - research is about asking a good question, finding the answer and arguing your conclusions - define the investigation - identify constructs and variables and what you are manipulating

Question 39

hypothesis

Answer 39

general statement of what will happen

Question 40

prediction

Answer 40

specific and in terms of your study

Question 41

theory

Answer 41

explains the predicted relationship in your study and is a coherent explanation or interpretation of one or more phenomena

Question 42

strategies for generating questions

Answer 42

- introspection: have a good think and come up with a question based on what you think about - find the exception to the rule: pposite of current research - a matter of degree - change the directionality

Question 43

characteristics of a good hypothesis

Answer 43

- testable and falsifiable - logical - a positive statement

Question 44

experimental research

Answer 44

- researchers who want to test hypotheses about causal relationships between variables (i.e., their goal is to explain) need to use an experimental method

Question 45

extraneous variables

Answer 45

any variable other than the dependant variable

Question 46

confounds

Answer 46

are a specific type of extraneous variable that systematically varies along with the variables under investigation and therefore provides an alternative explanation for the results

Question 47

nonexperimental research

Answer 47

researchers who are simply interested in describing characteristics of people, describing relationships between variables, and using those relationships to make predictions can use non-experimental research

Question 48

inferential statistics

Answer 48

allow researchers to draw conclusions about a population based on data from a sample

Question 49

statistically significant

Answer 49

an effect that is unlikely due to random chance and therefore likely represents a real effect in the population