What is the importance of training and development programs? What should managers consider in developing a training program?
What are some advantages and disadvantages (note at least two of each) of internal recruiting? Be specific in your response. Use examples.
After collecting the length data from all 150 female G. Holbrooki, A vertical life table was then built, since this data was collected from the population in one short-term occurrence. The age of the Mosquitofish was calculated using the following formula: age= 8*(standard length) -68, standard length being measured from snout to end of body, excluding tail. The mosquitofish were then categorized in age groups depending on their computed ages. It was necessary to calculate the number of individuals within each age class, which was computed using (s(x)). To compute the number of living individuals with each age class n(x)) was computed. The number of living individuals within the first age class was calculated using N0 = ∑nx. Every other age group was computed using Nx = (Nx-1) – (nx-1), which is essentially, the number of individuals in a previous age group subtracted from the number of individuals sampled in the age group. Survival rate was represented as (l(x)) and was computed as the number of individuals in an age group divided by the number of individuals alive in the first age class, which is represented by n(0). The formula used to compute fecundity is as follows (l(x)*b(x)) and it represents the amount of offspring produced by each particular age group. Highest age weighted fecundity was given by (l(x)*(b(x)*x). The net reproductive rate (R0) was computed using by the sum of the entire column of (l(x)*b(x)). Intrinsic growth rate (r) was computed using the division of the natural log and the net reproductive rate (R0) by the mean generation time (G). Mean generation time (G) was computed by taking the sum of the (l(x)*(b(x)*x) column and its division by the net reproductive rate (R0). The highest age-weighted fecundity given by (l(x)*(b(x)*x) age group was used to determine the optimal age of sexual maturity. Results A statistical test was ran for each respective life history aspect of R0, r, and G to test for statistical significance between the two temperatures. The net reproductive rate statistical test between the two temperatures gave a p value of much less than 0.05 (p-value = 1.97e-06). This signifies that the null hypothesis can be rejected. Concluding that net reproductive rate does have a significant difference between the two temperatures. For intrinsic growth rate the p value was also less than 0.05(1.778e-06) rejecting the null hypothesis. Intrinsic growth rate does exhibit a significant difference between the two temperatures. Mean generation time’s statistical test between the two seasons also resulted in a p-value of less than 0.05 (p-value < 2.2e-16). Concluding that mean generation time does exhibit a significant difference between the two temperatures. Intrinsic growth rate (r) and Net reproductive rate were found to have a strong POSITIVE linear correlation. Figures:>GET ANSWER