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Biostatistics Weeks 6&7 Notes

by: Kiara Lynch

Biostatistics Weeks 6&7 Notes BIO 472

Marketplace > La Salle University > Biology > BIO 472 > Biostatistics Weeks 6 7 Notes
Kiara Lynch
La Salle

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About this Document

These are notes from weeks 6 and 7 of class.
Class Notes
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This 0 page Class Notes was uploaded by Kiara Lynch on Thursday March 10, 2016. The Class Notes belongs to BIO 472 at La Salle University taught by in Summer 2015. Since its upload, it has received 20 views. For similar materials see Biostatistics in Biology at La Salle University.

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Date Created: 03/10/16
Biostat Weeks 67 notes If zero is not in the con dence interval then reject the null hypothesis and say the means are signi cantly different If zero falls in con dence interval then numbers are not signi cantly different p value measures likelihood of getting a result t statsitic give the null hypothesis is ture p value lt05 then result is unlikely and null hypothesis is rejected the difference between the means is signi cantly different If hypothetical mean is not 0 then see if other value ex30 is within con dence interval If it is do not reject null hypothesis mean is not signi cantly different libraryrgl xltseq120length1000 yltcosx zltsinx plot3dxyz BumpusltreadcsvquotbumpuscsvquotheaderT attachBumpus libraryrgl plot3dAlarExtentmm Femurin Skullin ske5 colquotbluequot Genderltc4987 pieGender pieGender colrainbow2 mainquotBirdsquot labelscquotFemalequotquotMalequot percentsltGendersumGender100 gives percents of each group percents roundedpercentsltroundpercents2 rounds percents to two decimals roundedpercents colsltcquotlightseagreenquotquotmediumvioletredquot create color palette Labelsltroundedpercents pieGender abesLabels colcols cex13 changes size of labels egendquottoprightquot creates legend at top right cquotFemalesquotquotMalesquot creates labels for legend llcols cex13 SexSurvivedlttableSexSurvived creates table for males and females that survived SexSurvived pieSexSurvived reads table top to bottom then to the right percsltSexSurvivedsumSexSurvived100 percs pieSexSurvived abesroundpercs0 colrainbow4 egendCTopNghF3 cquotDead FemalesquotquotDead MalesquotquotSurviving FemalesquotquotSurviving Males llrainbow4 labsltpasteroundpercs1quotquotsepquotquot puts sign after number pieSexSurvived abesabs A Primer on Experimental Design oExperimental Artifact bias in a measurement as result of unintended consequences from the experimental procedure 0 ex did not account for stress when conducting bird experiment on measuring heart rate when above water and when forced below water 0 0Confounding variables o proper controlled experiments seek to eliminate the effect of potential confounding factors 0 masks causal relationship among measured variables oObjectives of an experiment 0 reduce bias in estimatingtesting treatment effects control group group that does not receive treatment but experiences similar conditions as treatment groups placebo effect improvement in a medical condition that results from the psychological effects of a medical treatment randomization individuals are randomly assigned to treatment ip a coin draw names random gen breaks association bw potential confounding variables and potential treatment effect don39t ask for volunteers they would know what treatment they were getting gt no placebo effect groups will have confounding variables may appeal to certain group blinding which subjects receive which treatments is not known to the subjects andor the researchers singleblind experiment only subjects do not know which treatment they are receiving doubleblind experiment subjects and researcher do not know which groups are which 0 reduce sampling error in measurements and estimates replication increase reps reduces variability more precise estimate of a statistic balance keep sample sizes about the same smaller standard error equal amount of info for all groups precise estimate blocking group subjects by some potentially founding variables olnformation from previous researchplot study 0 pvalue 0 estimate mean difference standard deviation 0 determine which tstatistic will be signi cant using t distribution 0 use basic algebra Effect size Mean difference Standard deviation Cohen39s D Power measure of the ability to correctly reject the null hypothesis when it is false 1Ptype ll error Increasing power increases probability of a type I error d difference of meansstandard deviation create a list of 12 individuals dlt cquotBrianquotquotBobquotquotBriannaquotquotBriequotquotBriellequotquotBillquotquotBillyquotquotBettyquotquotBeatricequotquotB artquotquotBethquotquotBradquot Id sampled6 sampleobjectn these individuals are then the random assignment to one group the remainder are assigned to group 2 or sampleobject rearranges the list lst 6 in group 1 rest in group 2 if 3 groups then rst 4 go in group 1 second 4 in group 2 etc setseed1 gets same result every time it is ran sampleld setseed2 sampleld sampleld Random Uniform Probability Distribution runif30360 runifrandom values needed min max sample33603 sampleminmax values needed pwrttestdquoteffect sizequotsiglevelquotaphaquotpower8 typequottwosampequot or quotone samplequot or quotpairedquot alternativequottwwsidedquot or quotlessquot or quotgreaterquot librarypwr pwrttestd02 sigeve05 power08 nd min sample size to get high prob to reject null hypothesis typequottwosampequot alternativequottwosidedquot sampleld107 always round n value up or else you will decrease the power yltcrnormn107 mean0 sd1 two samples only changing mean rnormn107 mean08 sd1 xltcrepquotcontrolquot107 repquottreatmentquot107 repeat control value 26 times then repeat treatment value 26 times x ttestyx t test of y against x varequalT if the difference between the means is large you need a smaller sample size and vice versa


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