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64 Cards in this Set
- Front
- Back
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Qualitative Measurement
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measure data DURING data collection & analysis; convert data (words, symbols); inductive reasoning (concrete-> abstract)
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Quantitative Measurement
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measure variables BEFORE data collection; focus on convert data (#'s); deductive reasoning (abstract->concrete)
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Conceptualization
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process of carefully thinking through the meaning of a construct; VERY abstract
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operationalism
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process of defining a concept so that it can be measured & repeated; observations can be made that are reliable & valid; practical; links a conceptual definition to a specific set of measurement techniques or procedures; fit your measure to your specific conceptual definition to the practical constraints within which you must operate and to the research techniques you know or can learn; links the language of theory w/ the language of empirical measures
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Relability
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dependability or consistency; consistency in results of a test or measurement
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Validity
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capacity of an instrument to measure what it was designed to measure; truthfulness
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Quantitative: Improve Reliability
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conceptualize constructs-"designed to eliminate noise"; specfic level of measurement; use multiple indicators of a variable; adminster pretest/pilot test
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Quantitative: Improve Validity
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face validity; content validity; criterion validity; concurrent validity; predictive validity
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face validity
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(quantitative)definition & method of measuremen are good fit;a judgement by the scientific community that the indicator really measures the construct ie. not many people would accept 2 +2= 4 as a sufficient way to test a college student's math abilities
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content validity
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a special type of face validity; is the fully CONTENT of a definition represented in a measure?
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criterion validity
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outside source of measure will verify your validity; uses some standard or criterion to indicate a construct accurately
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concurrent validity
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type of criterion validity; doing well on one test you should do well on another
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predictive validity
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predict some future behavior; ie. SAT results are a predicator of whether you will do well in college
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Qualitative: reliability
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Data is an interactive process; bc it is collected in a unique process; consistency through interviews, participation, photographs, document studies; evolving relationship w/ subject matter
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Qualitative operationalization
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often precedes conceptualization; describes how specific observations and thoughts about the data contributed to working ideas that are the basis of conceptual definitions and theoretical concepts; an after-the-fact description (more than a before-the-fact preplanned technique); data gathering occurs w/ or prior to full operationalization; describes how the researcher collects data, but it includes the researcher's use of preexisting techniques & concepts that were blended w/ those that emerged during the data collection process
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Qualitative conceptualization
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a process of forming coherent theoretical definitions as one struggles to "make sense" or organize the data & one's preliminary ideas; refine rudimentary "working ideas" DURING the data collection and analysis process
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Quanitative conceptualization
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refining abstract ideas into theoretical definitions early in the research process
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Quantitative Operationalization
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(after conceptualization); developing an operational definition or set of indicators for it
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continuous variables
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(quantitative measurment)infinite # of values/attributes (along a continuum); can be made discrete --> temp by saying it's "cold" and "hot"; ratio/interval levels
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discrete variables
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(quantitative measurement) fixed set of values/attributes (marital status); can be made continuous--> temperature; nominal & ordinal levels
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Qualitative validity
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based on participants views & accounts; authenticity: assuming participants are giving the honest truth from their perspective (asking in multiple ways to know for sure if someone knows the material)
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nominal (level of measurement)
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categories by names (social class, race)
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oridinal (level of measurement)
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one is greater than another (letter grades; completely agree, agree, disagree);nominal too
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Interval (level of measurement)
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(oridinal & nominal too!) no absolute zero-> it's arbitrary; where you cannot say something is 3 or 4x bigger; ie. temperature (bc you have neg. degrees)
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ratio (level of measurement)
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(nominal, ordinal, interval too!)real zero; you can say something is 2x something else (ie. age, weight, $)
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scales
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measure of intensity, direction, level of a construct; oridinal: attitude (measured in continuum)
strongly agree <----> strongly disagree; likert is used most frequently |
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indexes
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measure that adds or combines several indicators; I or R; look @ weighted measure; cumulative score that is supposed to measure faculty member qualitiy by student perceptions
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good measurement
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mutually exclusive (only one possibility for an answer); exhaustive (all possible choices must be listed); unidimensional (within an index all scales should measure one construct)
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Literature Review
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scholarly journals, books, dissertations, gov't documents
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ethnography
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study on a community; studies on neighborhoods, street corners
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Quantitative(issue in research)
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linear path: logical sequence of path, rigid research question is much more narrowed & focused
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Qualitative (issue in research)
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circular path; flexible, you might get new ideas while researching and refine your approach, "How much" "How many"
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Qualitative research
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1. interpretations & meanings (many perspectives), inductive reasoning, empirical>observation, record, document, examine real events; 2. grounded in theory: "grounded in the data"-drives the theory & research question; 3. context-"the meaning", applied to a certain time, place, culture, setting you cannot move the situation out of the context; 4. cases of the unit of analysis(casual relationship), each individual becomes your unit of analysis; 5. interpretation (steps) a.participant's voice (record them verbatim) b. researcher as an "outsider" c. connect study to sociology
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Quantitative Research Methods
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variables, attributes, independent variable, hypothesis, level of analysis & unit of analysis, Types of error
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variables
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different concepts, looking @ relationships among different variables (race, ethnicity)
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attributes
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characteristics or categories of variables (ie. adolscence/young adulthood, male/female)
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independent variable
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cause leading to the dependent variable
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intervening variable
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ex. good parent support---> high self esteem (when actually, it's bc of good school performance)
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hypothesis
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able to predict a cause & effect relationship (edu. guess); linked to research question & theory; can be tested as false, but you cannot neccessarily test if a hypothesis is true
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null hypothesis
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test that there is no relationship bn the variables (no association)
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alternative hypothesis
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test that a relationship exists bn 2 variables
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level of analysis
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macro(social category or institution) & micro (unit individual)
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unit of analysis
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what level? individual, family, institutional, social categories
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ecological fallacy
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making an error in infering relationships bn 2 variables will also hold true at the individual level; assume some group behavior can be understood @ the individual level; ie. unemployment increases so does mental illness, so they must be related
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reductionism
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fallacy of non equivalence; using a psychological explanation; use 1 factor to explain a range of behaviors
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spuriousness
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no relationship bn the variables; each of those variables are correlated to a 3rd variable(has more impact, NOT casual); ie. consuming an herb & longevity--> 3rd variable = wealth
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to avoid error, your level of analysis =
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your unit of analysis!
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nonprobability sampling (qualitative) non random (4 types)
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Purposive sampling, snowball sampling, deviant case sampling, sequential sampling
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purposive sampling
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field research, exploratory, do not know if cases are selecting are representative of population (if possible you want to get every person in the population)
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snowball sampling
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researcher selects the cases from a network of people; start w/ 1 case that might lead to another case (indirect or direct links w/ individuals); used for further topics/referrals; very effective with "sensitive" topics
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Deviant Case sampling
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studying cases of different social patterns, that do not fit the general pattern; ie. highschool dropout whose parents went to grad. school
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sequential sampling
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researcher has acquired enough cases that he is satisfied (acquired the minimal #); * there is no way you can say that your sample is representative of the WHOLE subculture
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probability sampling
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(quantitative); always taking sample of larger population
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sampling frame
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specific list constructed to approximate the population
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parameter
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a characteristic of the larger population; summary measure of the entire population
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random
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everyone has an equal chance, good representative of entire population
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sampling error
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how much a sample deviates from being representitive of the population
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simple random probability sampling
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a random sample in which a reasearcher creates a sampling frame and uses a pure random process to select cases.
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simple random WITH replacement
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draw sample out, put it back; draw from SAME smple out
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simple random WITHOUT replacement
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draw sample out; draw another sample
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sampling distribution
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a distribution of different samples that shows the frequency of different sample outcomes from many separate random samples
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systematic sampling
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a type of random sampling in which a researcher selects every xth (ie. 9th) case in the sampling frame using sampling interval
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stratified sampling
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researcher divides population into strata (subpopulation), then draws a random sample from each subpopulation; used to control the size of population; every single category will be represented
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cluster sampling
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take a sample of an already existing cluster, then randomly select from that cluster
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