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AbstractCurrent scientific, technical, and management progress is characterized by the generation of a tremendous amount of data for analysis. This, in turn, poses a significant challenge: to effectively and efficiently extract meaningful information from the large volume of data. Two relatively young professions, computer science and statistics, are intimately linked in any response to the challenge. They have consequently become indispensable to scientific, technical, and management progress, occupying a position at its very heartComputer science and statistics have each been separately documented by many books as well as numerous papers. However, the interface of computer science and statistics, the area of their interaction, has been documented only in part. This paper begins characterization of the entire interface by providing a structure and an historical background for itA structure for the interface is introduced initially, followed by an historical background for the interface presented in two parts. First to be summarized is the evolution of the interface from an interweaving of the mechanical prerequisites to the computer and mathematical prerequisities to computer science and of the foundations for probability and statistics. Development of statistics prior to 1900 then is reviewed.

Major Speakers -- Networks of Quasi-Reversible Nodes -- The c — Server Queue with Constant Service Times and a Versatile Markovian Arrival Process -- Simulation Output Analysis for General State Space Markov Chains -- Models and Problems of Dynamic Memory Allocation -- Probabilistic Analysis of Algorithms -- Point Process Method in Queueing Theory -- Error Minimization in Decomposable Stochastic Models -- Computational Methods for Product Form Queueing Networks: Extended Abstract -- Networks of Queues, I Richard Muntz, Chairman -- Closed Multichain Product Form Queueing Networks with Large Population Sizes -- The Significance of the Decomposition and the Arrival Theorems for the Evaluation of Closed Queueing Networks -- On Computing the Stationary Probability Vector of a Network of Two Coxian Servers -- Performance and Reliability Donald Gross, Chairman -- Fitting of Software Error and Reliability Models to Field Failure Data -- Performance Evaluation of Voice/Data Queueing Systems -- Probabilistic Aspects of Simulation Peter Lewis, Chairman -- On a Spectral Approach to Simulation Run Length Control -- Generation of Some First-Order Autoregressive Markovian Sequences of Positive Random Variables with Given Marginal Distributions -- Testing for Initialization Bias in the Mean of a Simulation Output Series: Extended Abstract -- Queueing Models in Performance Analysis, I Daniel Heyman, Chairman -- Response Time Analysis for Pipelining Jobs in a Tree Network of Processors -- Mean Delays of Individual Streams into a Queue: The ?GIi/M/1 Queue -- Probabilistic Models in Performance Analysis of Computer Systems and Communication Networks Donald Gaver, Chairman -- Analysis and Design of Processor Schedules for Real Time Applications -- Modeling Real Dasd Configurations -- Bottleneck Determination in Networks of Queues -- Probabilistic Analysis of Algorithms Dave Liu, Chairman -- On the Average Difference Between the Solutions to Linear and Integer Knapsack Problems.

Probability and random variables -- Probability distributions -- Stochastic processes -- Queueing theory -- Queueing theory models of computer systems -- Estimation -- Hypothesis testing -- Appendix A. Statistical tables -- Appendix B. APL programs -- Appendix C. Queueing theory definitions and formulas.

ABSTRACTDesirable improvements in college‐level accounting pedagogy are now possible through the use of computer science technology that provides efficient student input using optical scanners or mark‐sense cards and permits information retrieval using direct access storage devices. Optimum application of this technology requires that students receive error analyses capable of increasing their level of retained knowledge and that instructors receive output which identifies student strengths as well as emerging weaknesses. Instructor output should also provide data for statistical evaluation of class sections.We have developed the COMPACT system in attempting to meet these needs. Our article deleneates the minimum computer configuration as well as the one currently in use. We discuss the contents of student and instructor feedback. Through examples we show the role of the input error analysis routines and demonstrate the use and current limitations of these routines in their ability to provide algorithmic error analysis. We then illustrate a heuristic set which, under certain circumstances, is required to analyze multi‐entry transactions occuring as subsets of student problem solution input. We conclude by indicating the probable extentions of our system both in terms of subject matter and computer hardware.