Ecology of the burrowing amphipod, Pontoporeia affinis, in Lake Michigan / by Wayne Paul Alley.

63 The geometric mean was used because it is a more conservative estimate of the theoretical mean and is not affected by extreme values to the same extent as the arithmetic mean. The geometric mean also gives smaller counts relatively more importance than they enjoyed in the computation of the arithmetic mean. The upper and lower limits were calculated in the previously described manner because this method eliminates the possibility of negative confidence intervals. The correlation coefficient was employed as the second method of analysis because it is a useful tool for measuring the degree of a relationship. The computer program written to compute the correlation coefficient was also designed to present the relationship graphically. The computer automatically rounded off the results in the construction of the graph so these values are printed in regularly spaced columns and rows. It is impossible to interpret the relative importance of these data points because each point may actually represent more than one value. These graphs merely show the trends of the relationships while the correlation coefficients indicate the degree of the relationship. The third method, that of multiple linear regression, is a useful statistical tool in the study of biological systems because it has the ability of mathematically removing the effects of confounding environmental factors. Stepwise multiple regression analysis has the additional feature of generating the multiple regression equation, variable by variable, in the order of their relative importance.

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Title
Ecology of the burrowing amphipod, Pontoporeia affinis, in Lake Michigan / by Wayne Paul Alley.
Author
Alley, Wayne Paul.
Canvas
Page 63
Publication
Ann Arbor, Mich. :: University of Michigan,
1968.
Subject terms
Amphipoda -- Michigan, Lake.

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"Ecology of the burrowing amphipod, Pontoporeia affinis, in Lake Michigan / by Wayne Paul Alley." In the digital collection Great Lakes Digital Library. https://name.umdl.umich.edu/4737944.0001.001. University of Michigan Library Digital Collections. Accessed May 18, 2025.
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