Ecological MethodologyEcological Methodology, Second Edition provides a balance of material on animal and plant populations, and teaches students of ecology how to design efficient tests in order to obtain maximum precision with minimal work. |
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Page 103
... regression to estimate the true density D for our study area . There is no reason to expect that a simple linear relation of this type will be suitable for all types of situations . Indeed , there is now a growing list of factors that ...
... regression to estimate the true density D for our study area . There is no reason to expect that a simple linear relation of this type will be suitable for all types of situations . Indeed , there is now a growing list of factors that ...
Page 458
... REGRESSION Linear regression theory , as developed in standard statistics texts , applies to the situation in which one independent variable ( X ) is used to predict the value of a dependent variable ( Y ) . In many ecological ...
... REGRESSION Linear regression theory , as developed in standard statistics texts , applies to the situation in which one independent variable ( X ) is used to predict the value of a dependent variable ( Y ) . In many ecological ...
Page 459
... Regression of log body weight and hind foot length for snowshoe hares . Three regressions can be calculated for these data . The two standard regressions of Y on X and X on Y are shown as solid lines . The functional or geometric mean ...
... Regression of log body weight and hind foot length for snowshoe hares . Three regressions can be calculated for these data . The two standard regressions of Y on X and X on Y are shown as solid lines . The functional or geometric mean ...
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Common terms and phrases
abundance aphids Appendix assumptions bias calculations capture Caughley census zone Chapter chi-square clumped coefficient of variation confidence interval confidence limits defined density estimate distance ecological ecologists END-OF-FILE Enter equal catchability equation estimate of population estimate population example Figure finite population FORMAT 2X formula frequency distribution index of dispersion line transect mark-recapture marked animals method n₁ nearest neighbor negative binomial distribution niche breadth niche overlap normal distribution null hypothesis Number of animals Number of individuals number of quadrats number of samples number of species observed obtained parameters Petersen plot Poisson distribution population density population estimate problem Program proportion quadrat counts random points random sampling ratio READ recaptures regression sample size sample sizes sampling unit Schnabel Seber second sample simple random sampling spatial pattern standard error statistical statistical population stratum study area survival rate Table techniques Total number transformation variable variance