Study your flashcards anywhere!

Download the official Cram app for free >

  • Shuffle
    Toggle On
    Toggle Off
  • Alphabetize
    Toggle On
    Toggle Off
  • Front First
    Toggle On
    Toggle Off
  • Both Sides
    Toggle On
    Toggle Off
  • Read
    Toggle On
    Toggle Off
Reading...
Front

How to study your flashcards.

Right/Left arrow keys: Navigate between flashcards.right arrow keyleft arrow key

Up/Down arrow keys: Flip the card between the front and back.down keyup key

H key: Show hint (3rd side).h key

A key: Read text to speech.a key

image

Play button

image

Play button

image

Progress

1/64

Click to flip

64 Cards in this Set

  • Front
  • Back
Qualitative Measurement
measure data DURING data collection & analysis; convert data (words, symbols); inductive reasoning (concrete-> abstract)
Quantitative Measurement
measure variables BEFORE data collection; focus on convert data (#'s); deductive reasoning (abstract->concrete)
Conceptualization
process of carefully thinking through the meaning of a construct; VERY abstract
operationalism
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
Relability
dependability or consistency; consistency in results of a test or measurement
Validity
capacity of an instrument to measure what it was designed to measure; truthfulness
Quantitative: Improve Reliability
conceptualize constructs-"designed to eliminate noise"; specfic level of measurement; use multiple indicators of a variable; adminster pretest/pilot test
Quantitative: Improve Validity
face validity; content validity; criterion validity; concurrent validity; predictive validity
face validity
(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
content validity
a special type of face validity; is the fully CONTENT of a definition represented in a measure?
criterion validity
outside source of measure will verify your validity; uses some standard or criterion to indicate a construct accurately
concurrent validity
type of criterion validity; doing well on one test you should do well on another
predictive validity
predict some future behavior; ie. SAT results are a predicator of whether you will do well in college
Qualitative: reliability
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
Qualitative operationalization
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
Qualitative conceptualization
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
Quanitative conceptualization
refining abstract ideas into theoretical definitions early in the research process
Quantitative Operationalization
(after conceptualization); developing an operational definition or set of indicators for it
continuous variables
(quantitative measurment)infinite # of values/attributes (along a continuum); can be made discrete --> temp by saying it's "cold" and "hot"; ratio/interval levels
discrete variables
(quantitative measurement) fixed set of values/attributes (marital status); can be made continuous--> temperature; nominal & ordinal levels
Qualitative validity
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)
nominal (level of measurement)
categories by names (social class, race)
oridinal (level of measurement)
one is greater than another (letter grades; completely agree, agree, disagree);nominal too
Interval (level of measurement)
(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)
ratio (level of measurement)
(nominal, ordinal, interval too!)real zero; you can say something is 2x something else (ie. age, weight, $)
scales
measure of intensity, direction, level of a construct; oridinal: attitude (measured in continuum)
strongly agree <----> strongly disagree; likert is used most frequently
indexes
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
good measurement
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)
Literature Review
scholarly journals, books, dissertations, gov't documents
ethnography
study on a community; studies on neighborhoods, street corners
Quantitative(issue in research)
linear path: logical sequence of path, rigid research question is much more narrowed & focused
Qualitative (issue in research)
circular path; flexible, you might get new ideas while researching and refine your approach, "How much" "How many"
Qualitative research
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
Quantitative Research Methods
variables, attributes, independent variable, hypothesis, level of analysis & unit of analysis, Types of error
variables
different concepts, looking @ relationships among different variables (race, ethnicity)
attributes
characteristics or categories of variables (ie. adolscence/young adulthood, male/female)
independent variable
cause leading to the dependent variable
intervening variable
ex. good parent support---> high self esteem (when actually, it's bc of good school performance)
hypothesis
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
null hypothesis
test that there is no relationship bn the variables (no association)
alternative hypothesis
test that a relationship exists bn 2 variables
level of analysis
macro(social category or institution) & micro (unit individual)
unit of analysis
what level? individual, family, institutional, social categories
ecological fallacy
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
reductionism
fallacy of non equivalence; using a psychological explanation; use 1 factor to explain a range of behaviors
spuriousness
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
to avoid error, your level of analysis =
your unit of analysis!
nonprobability sampling (qualitative) non random (4 types)
Purposive sampling, snowball sampling, deviant case sampling, sequential sampling
purposive sampling
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)
snowball sampling
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
Deviant Case sampling
studying cases of different social patterns, that do not fit the general pattern; ie. highschool dropout whose parents went to grad. school
sequential sampling
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
probability sampling
(quantitative); always taking sample of larger population
sampling frame
specific list constructed to approximate the population
parameter
a characteristic of the larger population; summary measure of the entire population
random
everyone has an equal chance, good representative of entire population
sampling error
how much a sample deviates from being representitive of the population
simple random probability sampling
a random sample in which a reasearcher creates a sampling frame and uses a pure random process to select cases.
simple random WITH replacement
draw sample out, put it back; draw from SAME smple out
simple random WITHOUT replacement
draw sample out; draw another sample
sampling distribution
a distribution of different samples that shows the frequency of different sample outcomes from many separate random samples
systematic sampling
a type of random sampling in which a researcher selects every xth (ie. 9th) case in the sampling frame using sampling interval
stratified sampling
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
cluster sampling
take a sample of an already existing cluster, then randomly select from that cluster