Chapter 12 Conducting & Reading Research Baumgartner et al Chapter 13 Inferential Data Analysis.

Chapter 12Conducting & Reading

ResearchBaumgartner et al

Chapter 13

Inferential Data Analysis



Review of statistical tests

• One sample t test• Two independent samples t test• Two dependent samples t test• ANOVA• One-way Chi-Square Test• Two-way Chi-Square Test



Example 1



Ferguson, Douglas C., Chuck E. Harp, Paul A. Opler, Richard S. Peigler, Michael Pogue, Jerry A. Powell, and Michael J. Smith. 1999. Moths of North America. Jamestown, ND: Northern Prairie Wildlife Research Center Home Page. http://www.npwrc.usgs.gov/resource/distr/lepid/moths/mothsusa.htm (Version 12DEC2003).

Why do butterflies and moths have eye spots?



Research hypothesis: Eye spots are a defense against moth-eating birds.

• Experiment:– Test effect of exposure to eye-spot

patterns on behavior of moth-eating birds.

• Sample:– N=16 moth-eating birds



• Method:– Test in a 2 chamber enclosure,

separated by a partition with a doorway. Birds are free to roam from chamber to chamber.

– Chamber 1 has plain walls, chamber 2 has eye-spot patterns painted on the walls.

– Birds are tested one-at-a-time by placing in the doorway in the center.

– Each bird left in box for 60 minutes.– Amount of time spent in each

chamber is recorded.



What are the independent and dependent variables?

• Independent: Chamber selected

• Dependent: Amount of time spent there.



What statistical test do we use?

• One sample t-test• H0: Birds show no preference for

either chamber– H0: µ = 30 (for room with spots)

• HA: Eye patterns affect behavior, but will they show avoidance or attraction?– HA: µ ne 30 (2-tailed test)

• Go to SPSS file to analyze



Alternative hypotheses, controls?

• Lighting in chambers• Time of day• Motivation (food deprivation)• Different or same species?



Example 2



Pharmacology example

• Assess effectiveness of new drug by noting concentration in blood and/or urine certain time points after giving

• Want to compare two types of aspirin (A and B)



• Experiment:– Test clearance of each type of aspirin

one hour after it is given

• Sample:– N=10 subjects

Research hypothesis: There is no difference in the effectiveness of the

two types of aspirin



• Method:– Randomly assign half the subjects to

receive aspirin A first and the other half to receive aspirin B

– Give same dosage of assigned aspirin to each subject

– Test amount of aspirin in urine 1 hour later

– One week later, after aspirin has cleared system, test each subject with the other aspirin




• Independent:– Type of aspirin

• Dependent:– Amount of aspirin in urine 1-hour later




• Two dependent samples sample t-test• H0: No difference in amount of drug in

system– H0: µA - µB = 0

• HA: There is a difference in amount of drug in system– HA: µA - µB ne 0 (2-tailed test)





• Differences in subjects body composition

• Differences in subjects eating/drinking habits

• Genetic differences in pharmacological response to aspirin



Example 3



Duncker’s Candle Problem

• 2 volunteers to leave room– Haven’t had class in cognitive

psychology



• Experiment:– Test length of time it takes subjects

to solve the problem.

• Sample:– N=20 subjects

Research hypothesis: It will take longer for subjects who are given

tacks in the box to solve the problem.



• Method:– Randomly assign half the subjects to

get tacks in the box and half to get tacks out of the box

– Measure how much time it takes each subject to solve the problem




• Independent:– Location of tacks

• Dependent:– Amount of time to solve problem




• Two independent samples t-test• H0: No difference between people

who get tacks in box or out of box– H0: µ1 - µ2 = 0

• HA: The group who gets the tacks in the box takes more time to solve– HA: µ1 - µ2 > 0 (1-tailed test)





• Attitude of researcher as box, tacks, candle are presented

• Differences in subjects educational background/IQ

• Differences in subjects age/gender

Chapter 12 Conducting & Reading Research Baumgartner et al Chapter 13 Inferential Data Analysis.

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