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Lecture 2

Lecture 2 - September 13 - LIFESCI 2A03

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Department
Life Sciences
Course Code
LIFESCI 2A03
Professor
Joe Kim

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LIFESCI 2A03 Lecture 2 September 13, 2013 Hypothesis  Hypothesis – a proposal or explanation  A scientific hypothesis – a proposal that makes a prediction; application of the scientific method allows one to test the hypothesis  Tentative explanations that account for observations  Hypotheses inevitably lead to predictions about the result of intervention  Predictions can be verified or refuted by analyzing the data  The formulation and testing of hypotheses is the basis of any scientific or rational inquiry Logic  Inductive Logic (induction) – inductive generalizations summarize a set of observations and serve to provide a prediction about unseen events; singularity to generality o Eg/ This ice is cold; therefore all ice is cold  Deductive Logic (deduction) – going beyond the formulation of hypotheses formed by induction to test whether they are correct involves the use of deductive logic; have generality, make hypothesis about singularity o Eg/ if all green apples are sour, then this green apple will be sour o A hypothesis is followed by a prediction:  If – (generalization)  Then – (specific instance you are testing)  This is called a deductive syllogism  The fact that this deductive syllogism lead to predictions means that hypotheses can be tested Logic, predictions and testing hypotheses  Truth Table o If you obtain a false prediction, the hypothesis must also be false – if the result is inconsistent with the prediction, you must reject the hypothesis o If you obtain a true prediction, the hypothesis may be true or false – true predictions do not constitute proof for the truth of the hypothesis, you fail to reject the hypothesis o Never say hypothesis is TRUE  hypothesis is good predictor, consistent with data, do not reject hypothesis o True prediction doesn’t tell much about truth of hypothesis; consistent or inconsistent with data  Null Hypothesis – statistical term (not simply the opposite of your hypothesis); simple way of saying that there is no (significant) difference between two sets of results o Eg/ A difference in observations between a control group and an experimental group in which you have introduced an intervention  Eg/ Regeneration; control = newt; experimental = add chemical to speed rate of regeneration  Null Hypothesis: there is no significance between chemical and rate of regeneration (two sets of results) o Eg/ Observations of two groups in two different conditions  Two populations of birds  Null Hypothesis: there is no significant difference between the two groups o Eg/ A set of predicted results and the observed results Case Study 1; Brain Freeze  If one thing is going to ruin a bowl of Ben and Jerry’s more than reading the ingredients label, its getting that searing ice cream headache. It’s almost enough to put you off having a second bowl. Almost enough, but not quite.  What is a brain freeze or ice cream headache?  Ice cream evoked headaches (ICE-H) study: randomized trial of accelerated versus cautious ice cream eating regimen  Kaczorowski, M and J. Kaczorowski. 2002. BMJ. 325(7378):1445-6.  Compared the effect of two ice cream eating regiments on the incidence of ice cream induced headaches  Hypothesis – If you eat ice cream quickly, there is a
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