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Quantitative Methods for Researchers Paul Cairns paul.cairns@york.ac.uk
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Your objectives Pretty general! – Landscape/area of experiments Research topic? 2
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My objectives Three pillars – Experimental design – Statistics – Writing up Need all three for good research 3
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Why do we do experiments? 4
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Philosophy of experiments Test theories Isolate phenomena Severely test 5
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Some consequences Intrinsic value Big is not always better Narrow focus is essential 6
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Experimental argument Belief:X causes Y – A reason for looking Try: change X and measure Y Analyse carefully Produce evidence 7
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Statistical experiments Natural variation – People, environment, stochastic Systematic vs chance differences No certainty 8
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Devising an experiment Research question (disposable) One sentence May use jargon Answer is “yes/no” but probably “maybe” Question suggests how to answer it QUAN, Paul Cairns
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Devise a research question In groups of two or three, each have a go at a research question. Take turns to explain and be criticised. Be happy to be wrong/stupid. RQs are disposable. QUAN, Paul Cairns
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Experimental Design Addresses question Validity Design => Data => Results 11
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Variables Independent variable (IV, X) – Experimental conditions Dependent variable (DV, Y) – quantitative Confounding variables 12
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Validity Construct –measuring DV – possible, meaningful? Internal – addressing question – confounds External - generalisability Ecological - realism 13
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Fantasy abstract Write an abstract for your experiment (150-250 words) specifying: 1.What the question is 2.[Why it is interesting/important] 3.What was done in the experiment What IV and DV are 4.What significant results [would] show 5.What this means 14
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Reading Hacking, Representing and Intervening Cairns, Cox, Research Methods for HCI: chaps 1, 6, 10 Harris, Designing and reporting experiments in psychology, 3rd edn 15
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