Previous font quickly module 5 arranging evidence to

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previous font quickly Module 5: Arranging Evidence to Support Arguments and Collecting Survey Data Ethically (and Right!) Notes Evidence, data, collection, and measurement error -Managing Error in Measurement -How much does it cost to measure… -The presence of Hadrons and other elementary particles? The characteristics and attitudes of Americans? -Accurate measurement is costly in all fields -Instrument: Large Hadron Collider; field: particle physics; measures: results of high-energy particle collisions; data scale: petabytes (10^15 byte); cost: approx $1 bill/yr -Instrument: General Social Survey; Field: multiple social sciences; Measure: approx 5000 social survey variables; data scale: megabyte (10^6 byte); cost: approx $2mil/yr -Classifying errors in measurement (and other errors) data: how to count what can be counted? -the discipline and method of measurement -in survey design the rule is: EVERY WORD MATTERS -asking q’s that measure what you actually want to measure (and responsibly) -requests for our “feedback” also abound -Those damn receipts, customer satisfaction surveys, marketing surveys, online surveys, telephone surveys, canvassers (where else have you encountered requests for a “few minutes of your time”? -Question: is there a downside to this technological ease in creating surveys? -An assertion to reflect upon: every survey or interview conducted with the general public has the potential to help or damage the ability of social science researchers to conduct serious scientific.(example. Push polls) -other reflections: writing survey and questionnaire items that avoid measurement bias is hard work -reducing measurement bias can often be very easy -it takes a bit of time and effort though Major tasks in measurement 1. Measure in a reliable way: should get same measurements over time 2. Measure in a valid way: measurements obtained should reflect reality w/little error 3. Measure in a precise way: should be as specific as possible How do we measure social concepts? 1.-Conceptualization: deciding what a concept “means” ; a collective endeavor by many researchers deciding the shared meaning of a specific term
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2.-Operationalization: deciding which of many specific ways of measuring the concept will be used (dimension) ; a decision by the researcher (often guided by experience/empirical data) 3.-Measurement: actually collecting the data and attempting to remove any remaining sources of error or bias ; carried out by the researcher and team -example. Measuring migration, using questions to explore concepts Measurement; common error sources : 1. Question wording (example: leading) 2. Bad choices (example: excluding options) 3. Coding (example: in translating answers into analyzable data) 4. Reactivity (common)(example: people change when they are being observed) 5. Validity problems (example: hypothesis guessing) 6. Fatigue(example: respondents tire, bore)(usually bc of question design) 7. Response set bias or straight-lining (example: checking straight down a column without reading each question
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