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135 Cards in this Set

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contigencency tables

unweidly for interval/ratio ( or even large ordinal) variables

mutivirate associations

1: independent


2: intervening


3: interactive


4: spurious

independent relationships

each X has an independent effect on Y

interveining relationships

all or part of an association between one variable to another is indirect


- a third variable intervenes between the two

interactive relationships

one variable changes the relationship between 2 others ,


- effects of X1 on Y varies by category of X2

spurious relationships

a false association between X1 and Y , caused by an antecedent variable, related to both

qualitative

inductive, interpretivists, often constructionist, use of naturalistic perspective

place of qualitative theory

grounded theory, interactive process

kinds of qualitative research

ethonography/particiapnt observation


focus groups, conversation/discourse analysis, textual and document analysis

main goals of qualitative research

1: empathy


2: in depth description and emphasis on context


3: emphasis on process


4: flexability and limited structure


empathy

seeing through the eyes of the people studied


involving probing beneath the surface of social behaviour

indepth description and emphasis on context

has narrow contexts, broader social context and cultural relativism

emphasis on process

showing how events and patterns unfold over time , a long time spent in the field allows the researcher to understand the indivala and social change

flexability and limited structure

questions asked the people studied tend to be quite general , especially early in the research

trustworhtiness characteristcis

1: crediability


2: transferability


3: dependability


4: confirmability

credability

parallels measurement and esp iternal validity


how believable are the findings ?

types of documents

1: personal documents


2: offical documents


3: mass media output


4: internet resources


personal documents

letters, diaries, photos

offical documents

gov. documents and private sources

mass media output

radio, Tv programs , newspapers

internet resources

web pages, chat rooms , etc

the most common method of qualitative approach is

a case study

approaches to coding

maifest and latent

manifest coding

emphasis on what is easily quantifiable/objective


- place of event , the country that the athlete represents , physical appearance, beauty , fashion etc

latent coding

semantic analyiss, emphasis is less straight forward, underlying meaning , more interpretive , portrayed as a complaint , passive, emotional , family centred. etc

element or a unit

a single case in the population , usually a person ,

population

the cases you would like to be able to say something about the cases from which you will select a sample



ex. could look at women of working age if wanted to find we want to look at which aspects of women current work lives impact family size in canada

sample

a # of units selected from the population from who data will be collected



ex. might be 1000 women of working age to whom we administer a survey

census

collecting data from all units in the population, not a sample

census is not a

sample

probability sampleing

sample selected using a random process , each unit in the population has a known probability of being sampled

non probability sample

a sample selected using a non random method

sampling frame

list of all units in your population from which a probability sample will be randomly selected

representative sample

contains the same distributions of characteristics as we see in the population , we need this to generalize our findings

sampling error

errors of estimation that occurs as a result of direness between the characteristics of the sample and those of the population

non - response

occurs if an element selected for the sample does not supply the required data

sampling related error

1: not using a random method to pick the sample


2: sampling frame


3: non response


sampling frame

isn't complete or is inaccurate, your frame does not reflect the population , so how can your sample?

non repsonse

occurs suh that those who participate in the study differ in some important way from those who do not

not using a random method to pick the sample

issuesof bias, ex. standing outside in the daytime interviewing students at western and picing who you want

probability samples

perferred in most research


- most likely to be representative


- can draw valid generations from our sample


- based on probability/sampling theory

non probability samples

perferred in exploratory research/pilot studies


- not random


-less likely to be representative


- cannot generalize beyond the sample


-limited info

simple random samples

most basic type of prob sample


- each unit has equal chance of selection ( sampling ratio works here)

how to select simple random sample

1: clearly define you population


2: devise a sampling frame for your pop


3: choose a sample size


4: # each unit of your frame from 1 - N


5: make a random # , none that are larger than N


6: each random # will correspond to a unit listen on your frame

stratified random sample

dividde population into subgroups , in our sampling frame , groups that we think are important to our study

systematic sample

- chose a pop, create a sampling frame and choose sample size , then select every 1th unit

whats a potential problem for systematic sample

periodicity

periodicity

if the cases int he sampling frame are arranged in some systematic order that corresponds to your sample interval

multi stage cluster sample

- used for sampling


- large populations


- populations where there is no proper sampling frame


-randomly sample these

trustworthiness characteristics

1: crediability


2: transferability


3: dependabiity


4: confirmability

credability

paralllels measurement and internal validity


- how believable are the findings

transferability

parallels external validity


-focus on thick descriptions


often look and compare rare cases

dependability

parallels reliability


-long and difficult ,not popular


-

confirmability

parallels replicability and objectivity


-

types of interviews

1: semi structured


2: unstrucutred


3: life history


4: survey ( structured)


5: focus groups


6: particiapnt obervation

semi strcutured

have a simple, changeable interview schedule , usually called an interview guide to guide the research

unstrucutred

have little or no interview schedule

life history

usually used with personal documents


- builds the story of one person or one family over the course of their lives


- usually retrospective


ex. sanchez family in mexico

survey structured interviews

standardization interviews sceduale


- clear bengingin and end


- often closed ended


professsional tone


interviewer is neutral

focus groups

in depth interviews


6-10 people


usually meet on one occasion , usually recorded

active role

doing what the subjects are doing


- sometimes can be physically dangerous ,illegal etc.

going nattive

when you genually join the subjects group you are studying


ex. white streets cornor society

access

1: open setting


2: closed setting


3: covert observaton


4: overt observation

open setting

public setting , parks down town etc

close setting

private or restricted setting ( meetings of private clubs etc

covert observation

people being studied do not know they are being observed by a researcher

overt observation

people being studied know they are being observed

how do you access closed settings or gain entre as a covert observer?

- need a sponsor ( someone to vouch for you), sometimes very difficult

sponsors can also serve as key informants

person who are particularly knowledegable and cooperative

drawbacks of key informants

- researcher may ignore other group memebrs


- views may not be representative of the group as a whole



- still need permission

ethnogaphic data ?

1: mental nots


2: jotted notes


3: direct observation notes


4: analytic memos


5: personal notes

mental notes

memory , when not possible to write anything down ex. during covert observation

jotted notes

written on the fly in the field , temporary reminders of whats happening as it unfolds

direct observation notes

recorded immediately after leaving the field


- ordered by date, time and place for each entry

analyitic memos

notes on how to proceed, typically involves theorretical insights

personal notes

for purposes of reflexivity ( feelings and emotional reactions to reaseach etc)

mode

most occurring value ,

mode

used in all types of data

mean

average

median

mid point in the distribution


-

median

used with interval ratio/ordinal but not nominal

nominal variables

composed of varibles that arent linked together

ordinal variables

can be ranked , words ex level of satisfaction

internal/ ratio

# ranked ex how depressed you are from 1-10 , continuous

standard deviation

measures of variation around the mean. effected by outliers

range

measured by measuring dispersions . diff b/w the may/min variable

contingency tables

most flexible for analyizing relationships

contingency tables

2 elements are analyzed , looks for patterns of association

in contingency tables % represents

independent variable

goals of quantitative research

systematic measurements

goals of quantitative research

establishing casualty

goals of quantitative research

generalization

goals of quantitative research

replication

systematic measuerment

measurment valdiity

establishing causality

internal validiityy

generalization

external validity

replication

standardization

goals of qualitative research

empathy

goals of qualitative research

indepth description and emphasis on context

goals of qualitative research

empahsis on process

goals of qualitative research

flexability and limited structure

sampling ratio

tells us what the chance is of being selected

sample weight

tells us how many cases in the population each sample unit represents

we can use the sample weight to define the

sampling interval for systtematic sample

each subgroup is sampled separately , but all use the same

sampling ratio

why is sample size very important?

- increasing sample quality and lowering sample error

as sample size increases

error decreases

temporarl order

the cause of an event must occur before the event being explained

why is temporal order relevant ?

for establishing time order , we need a why?

independent variable is the

explanatoy variable

dependent variable

is the response variable

how can we tell what is cause and what is effect?

1: temporarl order


2: assocation


3: eliminating alternatices ( spuriousness)

association between variables

one variable ( X) changes in conjunction with another ( Y)

reciprocial relationships

direction of causation between 2 variables moves in both directions

elminate ( rule out ) spurious relationships

apparent causal relationship ,

eliminate spurious relationships

ex. document an association between eating ice-cream and drowning

sufficent cause

is not necessary to produce an effect , but can produce an effect all by itself


- there can also be other potential causes

contribuitory cause

is neither a necessary nor sufficient cause of Y but changes the likelihood of Y occurring

univaritate

single variable

univariate

frequency tables, graphs, measures of central tendency, measures of dispersion

biviratie

contigency tables/cross tabs , tests of association

multivariate

types of associations

frequncy distributions

simple count across categories of a single variable - mutually exhaustive and exclusive


- possible with variables of all levels of measurement

% frequency

easier to understand the size difference between categories

IQV

for nominal variables


IQV

ranges between 0 and 1

IQV

0 if all the cases fall into a single category

IQV

1 if all the cases are equally distributed across categories

IQV stands for

index of qualitative research

what is good for any ranked variable

median

what is good is the categories are large

median

the higher the standard devation

the higher the vairablity of the mean

bar charts / histograms

good for nominal and ordinal variables and I/R if the variables are small

line graph / polygon

good for ordinal variables with lots of categories and I/R data

cumulative frequency distrbutions

% of cases in each category added to the % in proceeding categories , most useful for rank ordered variables