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UW-Madison STAT 371 - Chapter 8 Statistical Principles of Design

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The Big PictureCase StudiesEducation ExampleArabidopsis ExampleStarling Song ExampleDairy Diet ExampleWeight Loss StudyKey ConceptsConfoundingExperimental ArtifactsControl GroupsRandomizationBlindingReplicationBalanceBlockingChapter 8 Statistical Principles of DesignFall 2010Experimental DesignMany interesting questions in biology involve relationshipsbetween response variables and one or more explanatoryvariables.Biology is complex, and typically, many potential variables,both those measured and included in an analysis and thosenot measured, may influence the response variable of interest.A statistical analysis may reveal an association between anexplanatory variable and the response variable.It is very difficult to attribute causal effects to observationalvariables, because the true causal influence may affect boththe response and explanatory variable.However, properly designed experiments can reveal causes ofstatistical associations.The key idea is to reduce the potential effects of othervariables by designing metho ds to gather data that reducebias and sampling variation.Case StudiesWe will introduce aspects of experimental design on the basis ofthese case studies:An education example;An Arabidopsis fruit length example;A starling song length example;A dairy cow nutrition study;A weight loss study.Education ExampleExampleA researcher interested in biology education considers two differentcurricula for high scho ol biology. Students in one school follow astandard curriculum with lectures and assignments all from atextbook. Students in a second school have the same lectures andassignments, but spend one day each week participating in smallgroups in an inquiry-based research activity. Students from bothschools are given the same exam. Students with the standardcurriculum score an average of 81.2 and the group of students withthe extra research score an average of 88.6; hypothesis tests (botha permutation test and a two-independent-sample t-test) have verysmall p-values indicating higher mean scores for the extra researchgroup.Is there evidence to indicate that the supplementalinquiry-based research activity increases exam scores?Arabidopsis ExampleExampleA researcher conducts an experiment on the plant Arabidopsisthaliana that examines fruit length.a gene from a related plant is introduced into the genomes offour separate Arabidopsis plants;each of these plants is the progenitor of a transgenetic line.an additional Arabidopsis plant is included in the experiment,but does not have the trans-gene introduced;these five plants represent the T1 generation;each T1 plant is grown, self-fertilized, and seed is collected;a sample of 25 seeds from each plant are potted individually,grown, and self-fertilized;these plants are the T2 generation;the length of a sample of ten fruit is measured for each T2plant.Starling SongExampleStarlings are songbirds common in Wisconsin and elsewhere inthe United States.Male starlings sing in the spring from a nest area when theyattempt both to attract females as potential mates and tokeep other males away.Male starlings sing in the fall when they are in flocks of othermale birds.It is difficult to categorize a single song as “spring-like” or“fall-like”, but characteristics of song can be different at thetwo times.One simple song characteristic is the length of the song.In an experiment, a researcher randomly assigned 24 starlingsinto two groups of 12.Starling Song (cont.)ExampleAll measurements are taken in animal observation ro oms in aresearch lab oratory.The spring group was kept in a spring-like environment withmore light, a nest box, and a nearby female starling.The male group was kept in a fall-like environment with lesslight, no nest boxes, and in the proximity of other male birds.Each bird was observed and recorded for ten hours: birds sangdifferent numb ers of songs, and the length of each song wasdetermined.Each bird sang from between 5 and 60 songs.(In the actual study, characteristics of the songs beyond theirlength were of greater importance.)Dairy Cattle Diet ExampleExampleIn a study of dairy cow nutrition, researchers have access to20 dairy cows in a research herd.Researchers are interested in comparing a standard diet withthree other diets, each with varying amounts of alfalfa andcorn.In the experiment, the cows are randomly assigned to fourgroups of 5 cows each;Each group of cows receives each of the four diet treatmentsfor a period of three weeks; no measurements are taken thefirst week so the cow can adjust to the new diet.The diets are rotated according to a Latin Square design sothat each group has a different diet at the same time.Response variables include milk yield and abundance ofnitrogen in the manure.Latin Square DesignDiets are named A, B, C, and D. Each group of cows gets all fourdiets, but in different orders.Time PeriodGroup First Second Third Fourth1 A B C D2 C A D B3 B D A C4D C B AWeight-loss StudyExampleResearchers in the Department of Nutrition recruited 60overweight volunteers to participate in a weight loss study.Volunteers were randomly divided into two treatment groups.All subjects received educational information about diet.One treatment group was instructed to count and recordservings of each of several foo d types each day;the other treatment group was instructed to count and recordcalories consumed each day.Subjects were not aware of the instructions given to membersof the other group.ConfoundingDefinitionA confounding variable is a variable that masks or distorts therelationship between measured variables in a study or experiment.Two variables are said to be confounded if their effects on aresponse variable cannot be distinguished or separated.1What are possible confounding variables that may explain thedifferences in test scores in the education example?2What potential confounding factors are researchers trying toavoid with the Latin square design for the dairy cow nutritionstudy?3What are potential confounding factors in the weight lossexample?Experimental ArtifactsExampleAn early experiment finds that the heart rate of aquatic birds ishigher when they are above water than when they are submerged.Researchers attribute this as a physiological response to conserveoxygen. In the experiment, birds are forcefully submerged to havetheir heart rate measured. A later experiment uses technology thatmeasures heart rate when birds voluntarily submerge, and finds nodifference in heart rates between submerged


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UW-Madison STAT 371 - Chapter 8 Statistical Principles of Design

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