Although male elephants are capable of reproducing by 14 to 17 years of age, your adult males are usually unsuccessful in competing with their larger elders for the attention of receptive females. Since male elephants continue to grow throughout their lifetimes, and since larger males tend to be more successful at mating, the males most likely to pass their genes to future generations are those whose characteristics enable them to live long lives. Joyce Poole studied a population of African elephants in Amboseli National Park, Kenya, for 8 years. This data frame contains the number of successful matings and ages (at the study's beginning) of 41 male elephants.
A data frame with 41 observations on the following 2 variables.
Age of elephant at beginning of study
Number of successful matings
Ramsey, F.L. and Schafer, D.W. (2002). The Statistical Sleuth: A Course in Methods of Data Analysis (2nd ed), Duxbury.
Poole, J.H. (1989). Mate Guarding, Reproductive Success and Female Choice in African Elephants, Animal Behavior 37: 842–849.
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str(case2201) attach(case2201) ## EXPLORATION AND MODEL BUILDING plot(Matings ~ Age, log="y") ageSquared <- Age^2 myGlm1 <- glm(Matings ~ Age + ageSquared, family=poisson) summary(myGlm1) # No evidence of a need for ageSquared ## INFERENCE AND INTERPRETATION myGlm2 <- update(myGlm1, ~ . - ageSquared) summary(myGlm2) beta <- myGlm2$coef exp(beta) #1.071107 exp(confint(myGlm2,2)) #1.042558 1.100360 # Interpretation: Associated with each 1 year increase in age is a 7% increase # in the mean number of matings (95% confidence interval 4% to 10% increase). ## GRAPHICAL DISPLAY FOR PRESENTATION plot(Matings ~ Age, ylab="Number of Successful Matings", xlab="Age of Male Elephant (Years)", main="Age and Number of Successful Matings for 41 African Elephants", pch=21, bg="green", cex=2, lwd=2) dummyAge <- seq(min(Age),max(Age), length=50) lp <- beta + beta*dummyAge curve <- exp(lp) lines(curve ~ dummyAge,lwd=2) detach(case2201)