Flashcards
Week 3
Cards in this deck (19)
- 1Validityhow well a measuring devise measures what is it supposed to.
how well the operational definition matches the conceptual definition - 2Reliabilitya measuring is reliable if it consistently gives us the same answer.
measured through stability, internal consistency and equivalency
is a necessary condition for validity
= operational definition - 3Kinds of error in Operational Definitions:systematic
random - 4Systematic Errorconsistently not measuring what we think we are.
operational definition doesn't represent conceptual definition well
problem with validity - 5Random Errorif random error in operational definitions is controlled, the measure (exam/survey) will be more reliable.
- 6∑SUM
- 7μPOPULATION MEAN
- 8x̄ or σSAMPLE MEAN
- 9NPOPULATION
- 10nSAMPLE
- 11Populationentire group or class group being studied
- 12Samplesubjects of population that represents its population well
- 13Parametervalue that describes a population
- 14Statisticvalue that describes a sample
- 15Descriptive Statistics:[mean] statistical measure that takes one score that represents the information as a whole
- 16Inferential Statisticstechniques that allow us to study a sample then generalize it to the population
—can help us generalize about the populations from which samples were selected
—can tell us how likely it is that the differences between samples reflect real differences between populations - 17Non Probability Sampling (cannot calculate sampling error, try to avoid)choose who is available [doesn't necessarily represent population you are talking about]
unqualified volunteer sample
purposive sample [survey those who relate to survey]
quota sampling
snowball sample [survey those who know people who have taken it] - 18Probability Sampling (can calculate sampling error)random sampling: everyone has an equal chance of being selected to respond
systematic random sampling
stratified sampling
multistage sampling - 19Central Limit Theoremthe average/sum of a large bunch of measurements follows a normal bell curve even if the individual measurements do not
applies to distribution of sample means for ANY population
don't need large sample size before distribution is almost perfect (n=30)
can tell how much sampling error we have based on the relationship between samples and the normal curve
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- Media and Journalism Flashcards on Week 3, created by Cassandra Solarte on 10/10/2017.
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- Cassandra Solarte
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