Experimental Design and Data Analysis in the Life Sciences
Listed in: Biology, as BIOL-210
Moodle site: Course (Guest Accessible)
Stephen A. George (Section 01)
Organisms--even members of the same species--differ from one another in structure, genetics, physiology, biochemistry, and behavior. Life scientists’ observations contain variability not only because of measurement error or imprecision, but also because of real differences within the samples being studied. How is this variation best described quantitatively? What inferences about a population can be made from measurements on a sample of the population? If our aim is to detect differences between groups, such as experimental and control groups, how do we go about designing a study that has a reasonable chance of finding a meaningful difference if one exists, subject to considerations of time and cost? How is experimental design affected by ethical considerations in the treatment of animal and human subjects? Once the data are obtained, how likely is it that an observed difference between experimental and control groups could have arisen by chance because of variability in the samples chosen for study even if there were no actual effect of the experiment? The course will include study of the principles and methods of data analysis, practice in using these methods, and discussion of examples of successes and failures in the design of experiments and the use of statistics.
Not open to first-year students. Spring semester. Professor S. George.
KeywordsScience & Math for non-majors, Quantitative Reasoning
Offerings2015-16: Not offered
Other years: Offered in Spring 2013