Developing Hypotheses

Developing Hypotheses - &Ideas 17:36...

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Developing Hypotheses & Ideas 17:36 Evaluation & communication Is the final product worthy of being reported to the scientific community? Are the conclusions accurate, possible to replicate, and relevant to others? Four ways to insure high quality research 1. Impartial systematic  observation: logically sound experimental design  (random sampling, counterbalancing) 2. Use of appropriate quanitative methods: appropriate descriptive and  inferential statistics measures are reliable, valid, precise, accurate 3. Use of reason and logic: to draw appropriate conclusion 4. Presented in an appropriate perspective: and context, Scientist, participant,  witness, (i.e. be aware of your audience) The numbers game Construct: hypothetical factor that cannot be observed directly but is inferred from a  given behavior/circumstance Example: hunger, mental imagery, conflict center Variable: any characteristic/item that can take on more than one value Examples: speed, level of hostility, accuracy of feedback, reaction time Measurement: a process by which we assign numbers to indicate the amount of some  variable present (using some rule) But what are we doing when we measure? Simply assigning numbers to objects? Learning something about the object or is it properties? Doing something to the object itself?
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Measurement is a mathematical procedure Measurement relies on the assumption that an isomorphism exists between the abstract  mathematics and the objects being measured That is, between the formal relations and the empirical observations Does any rule, imply measurement (players’ number assignment) Rules are based on theoretical premises, not data themselves MEASUREMENT DOES NOT EQUAL DATA (phenomenon) Objective measurement: the hallmark of science Must show people how to replicate what you did Should produce the same result no matter who does the measurement Controlling measurement error Anything that leads to inconsistency in the measurement process can produce  measurement error Response set biases (e.g. social desirability) will add measurement error to any self- report measure “fuzzy” or vague measurement will also result in error operational definitions (measures) the specific procedures by which the researcher quantifies and/or manipulates a  variable In research, every material should be operationally defined The more careful and complete the operational definition, the more precise the  measurement of the variable will be Reliability How consistent your measurement is Observed score = test ability + error Types of reliability
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Interrater reliability: degree of agreement between two independent raters
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