Research Methods Final Exam

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contigencency tables

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

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mutivirate associations

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1: independent

2: intervening

3: interactive

4: spurious

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independent relationships

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each X has an independent effect on Y

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interveining relationships

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

- a third variable intervenes between the two

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interactive relationships

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one variable changes the relationship between 2 others ,

- effects of X1 on Y varies by category of X2

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spurious relationships

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

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qualitative

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inductive, interpretivists, often constructionist, use of naturalistic perspective

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place of qualitative theory

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grounded theory, interactive process

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kinds of qualitative research

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ethonography/particiapnt observation

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

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main goals of qualitative research

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1: empathy

2: in depth description and emphasis on context

3: emphasis on process

4: flexability and limited structure

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empathy

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seeing through the eyes of the people studied

involving probing beneath the surface of social behaviour

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indepth description and emphasis on context

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has narrow contexts, broader social context and cultural relativism

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emphasis on process

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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

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flexability and limited structure

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

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trustworhtiness characteristcis

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1: crediability

2: transferability

3: dependability

4: confirmability

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credability

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parallels measurement and esp iternal validity

how believable are the findings ?

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types of documents

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1: personal documents

2: offical documents

3: mass media output

4: internet resources

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personal documents

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letters, diaries, photos

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offical documents

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gov. documents and private sources

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mass media output

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radio, Tv programs , newspapers

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internet resources

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web pages, chat rooms , etc

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the most common method of qualitative approach is

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a case study

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approaches to coding

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maifest and latent

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manifest coding

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emphasis on what is easily quantifiable/objective

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

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latent coding

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

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element or a unit

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a single case in the population , usually a person ,

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population

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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

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sample

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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

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census

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

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census is not a

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sample

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probability sampleing

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

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non probability sample

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a sample selected using a non random method

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sampling frame

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

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representative sample

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

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sampling error

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

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non - response

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

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sampling related error

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1: not using a random method to pick the sample

2: sampling frame

3: non response

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sampling frame

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

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non repsonse

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

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not using a random method to pick the sample

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

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probability samples

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perferred in most research

- most likely to be representative

- can draw valid generations from our sample

- based on probability/sampling theory

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non probability samples

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perferred in exploratory research/pilot studies

- not random

-less likely to be representative

- cannot generalize beyond the sample

-limited info

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simple random samples

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most basic type of prob sample

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

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how to select simple random sample

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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

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stratified random sample

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

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systematic sample

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

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whats a potential problem for systematic sample

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periodicity

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periodicity

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

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multi stage cluster sample

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- used for sampling

- large populations

- populations where there is no proper sampling frame

-randomly sample these

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trustworthiness characteristics

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1: crediability

2: transferability

3: dependabiity

4: confirmability

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credability

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paralllels measurement and internal validity

- how believable are the findings

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transferability

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parallels external validity

-focus on thick descriptions

often look and compare rare cases

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dependability

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parallels reliability

-long and difficult ,not popular

-

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confirmability

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parallels replicability and objectivity

-

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types of interviews

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1: semi structured

2: unstrucutred

3: life history

4: survey ( structured)

5: focus groups

6: particiapnt obervation

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semi strcutured

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

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unstrucutred

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have little or no interview schedule

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life history

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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

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survey structured interviews

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standardization interviews sceduale

- clear bengingin and end

- often closed ended

professsional tone

interviewer is neutral

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focus groups

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in depth interviews

6-10 people

usually meet on one occasion , usually recorded

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active role

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doing what the subjects are doing

- sometimes can be physically dangerous ,illegal etc.

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going nattive

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when you genually join the subjects group you are studying

ex. white streets cornor society

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access

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1: open setting

2: closed setting

3: covert observaton

4: overt observation

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open setting

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public setting , parks down town etc

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close setting

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private or restricted setting ( meetings of private clubs etc

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covert observation

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

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overt observation

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people being studied know they are being observed

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

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

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sponsors can also serve as key informants

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person who are particularly knowledegable and cooperative

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drawbacks of key informants

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- researcher may ignore other group memebrs

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

- still need permission

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ethnogaphic data ?

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1: mental nots

2: jotted notes

3: direct observation notes

4: analytic memos

5: personal notes

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mental notes

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

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jotted notes

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

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direct observation notes

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recorded immediately after leaving the field

- ordered by date, time and place for each entry

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analyitic memos

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notes on how to proceed, typically involves theorretical insights

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personal notes

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

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mode

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most occurring value ,

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mode

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used in all types of data

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mean

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average

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median

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mid point in the distribution

-

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median

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used with interval ratio/ordinal but not nominal

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nominal variables

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composed of varibles that arent linked together

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ordinal variables

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can be ranked , words ex level of satisfaction

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internal/ ratio

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

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standard deviation

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measures of variation around the mean. effected by outliers

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range

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

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contingency tables

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most flexible for analyizing relationships

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contingency tables

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2 elements are analyzed , looks for patterns of association

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in contingency tables % represents

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independent variable

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goals of quantitative research

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systematic measurements

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goals of quantitative research

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establishing casualty

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goals of quantitative research

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generalization

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goals of quantitative research

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replication

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systematic measuerment

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measurment valdiity

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establishing causality

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internal validiityy

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generalization

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external validity

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replication

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standardization

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goals of qualitative research

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empathy

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goals of qualitative research

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indepth description and emphasis on context

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goals of qualitative research

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empahsis on process

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goals of qualitative research

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flexability and limited structure

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sampling ratio

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tells us what the chance is of being selected

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sample weight

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

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we can use the sample weight to define the

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sampling interval for systtematic sample

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each subgroup is sampled separately , but all use the same

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sampling ratio

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why is sample size very important?

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- increasing sample quality and lowering sample error

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as sample size increases

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error decreases

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temporarl order

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

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why is temporal order relevant ?

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for establishing time order , we need a why?

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independent variable is the

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explanatoy variable

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dependent variable

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is the response variable

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

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1: temporarl order

2: assocation

3: eliminating alternatices ( spuriousness)

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association between variables

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

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reciprocial relationships

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direction of causation between 2 variables moves in both directions

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elminate ( rule out ) spurious relationships

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apparent causal relationship ,

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eliminate spurious relationships

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

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sufficent cause

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

- there can also be other potential causes

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contribuitory cause

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

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univaritate

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single variable

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univariate

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

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biviratie

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contigency tables/cross tabs , tests of association

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multivariate

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types of associations

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frequncy distributions

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

- possible with variables of all levels of measurement

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% frequency

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easier to understand the size difference between categories

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IQV

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for nominal variables

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IQV

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ranges between 0 and 1

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IQV

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0 if all the cases fall into a single category

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IQV

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1 if all the cases are equally distributed across categories

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IQV stands for

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index of qualitative research

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what is good for any ranked variable

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median

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what is good is the categories are large

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median

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the higher the standard devation

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the higher the vairablity of the mean

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bar charts / histograms

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

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line graph / polygon

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

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cumulative frequency distrbutions

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