Final

Front 1

Non-probability

Back 1

samples are NOT selected using random sampling, reliance on available subjects, purposive or judgmental sampling

Front 2

Probability

Back 2

is based on random sampling

Front 3

Purposive or judgmental sampling

Back 3

Based on - researcher’s knowledge of the population, Purpose of study

Front 4

Snowball sampling

Back 4

Starts small, gets bigger, Initial sample leads to additional observations, Appropriate for difficult populations, Start with a small and accessible target population

Front 5

Quota sampling

Back 5

Matrix of important characteristics of a population, Determine the proportion of the population in each cell

Front 6

Disadvantages of non-probability sampling

Back 6

Sampling bias, Conscious or non-conscious, Lack of representativeness, Average of the sample DOES NOT closely approximate average of the population

Front 7

Theoretical Population

Back 7

what you really want, what your ideal population would be. Ex. one student from each school in each country

Front 8

Accessible Population

Back 8

what you actually got your hands on. Ex. a few students from each region

Front 9

Parameter

Back 9

summary description of a given variable in the population Ex. mean income of all families of UGA undergrads

Front 10

Stratified sampling

Back 10

Organize the population into homogenous subsets in order to select appropriate number of elements from each subset

Front 11

Multistage Cluster sampling

Back 11

Large population makes an exhaustive list impossible or impractical. Ex. All church members in the US.

Front 12

Sampling Frame

Back 12

list of all the elements (unit analysis) used to select your sample. If you do not have a sampling frame, you cannot do probability sampling. Ex. Poll UGA student body concerning changes to North Campus tailgating policy.

Front 13

Sampling error

Back 13

degree of disconnect between the statistic and parameter

Front 14

Sampling design

Back 14

refers to the rules and procedures by which the populations are included in the sample

Front 15

Random

Back 15

Everyone has a equal chance of being selected

Front 16

Components of Classic Experimental design

Back 16

Independent and dependent variable, random assignment, pre and post testing, experimental and control groups.

Front 17

Independent variable

Back 17

predicts outcomes put forth in hypothesis (cause)

Front 18

Dependent variable

Back 18

consequent variable (effect)

Front 19

Experimental group

Back 19

receives the stimulus (IV)

Front 20

Control group

Back 20

do not receive the stimulus, point of comparison

Front 21

Random assignment

Back 21

Eliminates the threat of selection bias, because the researcher uses probability sampling to determine who is in the experimental group and who is in the control group (the participants themselves DO NOT self-select exposure to the independent variable)In order to isolate the effect of the independent variable, we must randomly assign participants into each group

Front 22

Manipulation Check

Back 22

in experimentation, the researcher should check to determine whether the intended independent variable was manipulated appropriately

Front 23

Internal validity

Back 23

conclusions drawn from the experimental results may not accurately reflect what has gone on in the experiment itself

Front 24

External validity

Back 24

generalizability of experimental findings to the real world

Front 25

Quantitative data analysis

Back 25

Techniques researchers use to convert data to numerical form

Front 26

Qualitative data

Back 26

data whose form is textual, non numerical. Typically gathered by researchers who come from interpretivist or critical paradigms of knowing

Front 27

Univariate

Back 27

one variable

Front 28

Bivariate

Back 28

two variables simultaneously

Front 29

Descriptive statistics

Back 29

statistical computations describing the characteristics of a sample. Descriptive statistics merely summarize a set of sample observations.

Front 30

Inferential statistics

Back 30

the body of statistical computations relevant to making inferences from findings based on sample observations to some larger population

Front 31

Alternative hypothesis (H1)

Back 31

there is a relationship between variables

Front 32

Null hypothesis (Ho)

Back 32

There is no statistical relationship between variables

Front 33

"Statistically significant"

Back 33

If p < .05, “reject the null”

Front 34

Components included in a full research article

Back 34

Introduction, Lit Review, Hypotheses, Method Section, Results Section, Discussion Section, References, Appendix

Front 35

Non-participant observation

Back 35

the researcher watches the subjects of his or her study, with their knowledge, but without taking an active part in the situation under scrutiny

Front 36

Participant observation

Back 36

method employed in qualitative research to study communication phenomena in their natural settings. The researcher can adopt any of several roles in the field.

Front 37

Characteristics of focus group research

Back 37

Less control, Require skilled moderators, Can be difficult to analyze

Front 38

Purposes of qualitative interviewing

Back 38

Phenomena not directly observable, detailed cognitive processes, language use

Front 39

Phenomenology

Back 39

Approach researcher would take where focus in on participants’ personal experience, remove personal opinion and bias, no judgment

Front 40

Interpretivism

Back 40

Hold on to judgments and predictions as a researcher

Front 41

Three forms of interview protocols

Back 41

Structured (not qualitative), Semi-structured, Unstructured

Front 42

Practices

Back 42

socially recognized talk or action. Ex. delivering bad news, providing social support

Front 43

Episodes

Back 43

dramatic events. Ex. divorce, natural disasters

Front 44

Encounters

Back 44

people meeting and interacting. Ex. interviews, bus-stop conversation

Front 45

Relationships

Back 45

between people in social roles. Ex. mother-child, spousal communication

Front 46

Focus of qualitative interviewing

Back 46

Understanding meanings and rules for meaning making

Front 47

Description of qualitative interviewing

Back 47

Asking in a flexible and continuous manner, Primarily participant talking, Digging for detailed information.

Front 48

Nominal

Back 48

Most simplistic level, Nominal = Names, Categorical, Ex. Biological sex – Male and Female (Names, no Numbers), Religious affiliation, Political affiliation

Front 49

Ordinal

Back 49

Rank ORDER logically, Levels represent more or less of variable, Distance between levels doesn’t matter, Ex. Class Status, Level of education

Front 50

Interval

Back 50

Distance between attributes or levels must have meaning, Tells how much, Standardized intervals between each level, Specific number, Ex. Temperature (60 degrees is twice as warm as 30 degrees), IQ Scores

Front 51

Ratio

Back 51

Most sophisticated level, Distance between attributes or levels must have meaning, PLUS - Based on a true zero point, you can have a complete absence of the variable. In social science, we tend to view things as ration rather than interval

Front 52

Continuous measure

Back 52

increases steadily in tiny fractions, MEAN

Front 53

Discrete (Categorical)

Back 53

one category or another without middle steps, MODE

Front 54

Continuous hypothesis

Back 54

stating change along a continuum

Front 55

Directional hypothesis

Back 55

states the direction of the difference

Front 56

Nondirectional hypothesis

Back 56

states there will be a difference

Front 57

Difference hypothesis

Back 57

compare two attributes of the IV

Front 58

Three criteria for causality

Back 58

Time order (cause before effect, Correlation (have to be related), Non-spurious relationship (no outside factor)

Front 59

Structured interview

Back 59

The same questions are asked in the same way, same order for all participants

Front 60

Semi-structured interview

Back 60

Researcher works with suggested questions whose wording and arrangement can vary from one participant to another

Front 61

Unstructured interview

Back 61

Researcher has few, if any, pre-fomulated questions

Front 62

The Complete-Partcipant role

Back 62

participants lack awareness of being observed

Front 63

Participant as observer

Back 63

the researcher participates in the activities of the group, with group members aware of researcher

Front 64

Observer as participant

Back 64

researcher has minimal involvement with group members and they are aware of the role

Front 65

Complete observer

Back 65

researcher observes the group with no participation, unaware of observation