I. Introduction. The purpose of this paper is to discuss functions defined on the continuous sample paths of Gaussian Markov processes which serve as Green’s functions for pairs of generalized Schroedinger equations. The results extend the author’s earlier paper [2] to a forward time version, and consider different boundary conditions.
This paper considers a collective risk model formed linearly from four stochastic processes. The first process involves random sums of random variables, and portrays the insurance claims. The other three processes are Ornstein-Uhlenbeck processes which serve as models for the random deviations in assumptions about investment performance, operating expenses, and lapse expenses. The model presented earlier (Beekman 1975b(Beekman , 1976 is improved by using both calendar and operational times. Ornstein-Uhlenbeck distributions for finite time periods are derived, and tables are furnished. Probabilities of extreme deviations for the multi-risk process are discussed. The examples in (Beekman 1975b(Beekman , 1976 are reconsidered, and made more realistic by an improved treatment of the time variables.
This paper examines the graduation rates between 2000 and 2015 of United States colleges and universities at the national, state, and institutional levels. This research focuses on two-year and four-year programs. Rates are investigated longitudinally along with variables that distinguish between public/private institutions, percentages of full-time and part-time enrollments, a variety of completion times, and levels of academic achievement at entry that include SAT scores and high school GPAs. The paper uses a logistic growth function that has been used by other researchers to model four-, five-, and six-year graduation rates of individuals and selected cohort groups; graduation rate trajectories for students of differing academic achievement backgrounds are projected into the future to demonstrate maximum graduation rates expected for entering cohorts. Included is the analysis of national, state, and institutional graduation-rate results in four-year institutions of the 50 states; examples from 14 public colleges and universities in Indiana and several surrounding states are also considered. In addition to fitting their graduation rates to the logistic function and extracting associated growth variables, we use percentages of part-time students to predict two- and four-year graduation rates at the national, state, and institutional levels in the 50 states. The analysis examined the graduation rates between 2000 and 2015 of United States colleges and universities and showed no correlation between a state’s two-year and four-year cohort graduation rates; verified an inverse mathematical relationship between graduation rates and percentage of part-time students; confirmed that for median SAT scores of 800 or lower one expects very low on-time graduation rates.
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