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Adrianne L. Jenner; Pamela M. Burrage – International Journal of Mathematical Education in Science and Technology, 2024
Mathematics provides us with tools to capture and explain phenomena in everyday biology, even at the nanoscale. The most regularly applied technique to biology is differential equations. In this article, we seek to present how differential equation models of biological phenomena, particularly the flow through ion channels, can be used to motivate…
Descriptors: Cytology, Mathematical Models, Prediction, Equations (Mathematics)
Amel Awadelkarim – ProQuest LLC, 2023
With the rise in popularity of social media and e-commerce platforms, "discrete math" is at the heart of our online experiences, playing a front-end role in the recommendation of what to click, watch, or buy, or who to follow or friend, as well as a back-end role in data storage, access, and transfer. This thesis focuses on two such…
Descriptors: Algorithms, Mathematical Models, Statistics, Mathematical Applications
Yaw Marfo Missah; Fuseini Inusah; Ussiph Najim; Frimpong Twum – SAGE Open, 2023
The major challenge of most basic schools is inadequate educational resources despite a conscious effort to constantly provide. This is a result of inaccurate data management leading to inappropriate predictions for effective planning. The actual efficiency of a system is determined by its ability to predict real-life data with speed and accuracy.…
Descriptors: Mathematical Models, Information Management, Educational Resources, Artificial Intelligence

Baker, Bruce D.; Richards, Craig E. – Economics of Education Review, 1999
Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…
Descriptors: Algorithms, Econometrics, Elementary Secondary Education, Expenditure per Student
Tracz, G. S.; Burtnyk, W. A. – 1972
To fully develop a teacher cost model, it is essential to be able to forecast the number of teachers that leave the experience category distribution -- not only the total number that leave, but also the number that leave from each category and experience level within the distribution. Similarly, it is essential to be able to forecast, to the same…
Descriptors: Algorithms, Costs, Mathematical Models, Prediction
Butler, Ronald W. – 1985
The dynamic linear model or Kalman filtering model provides a useful methodology for predicting the past, present, and future states of a dynamic system, such as an object in motion or an economic or social indicator that is changing systematically with time. Recursive likelihood methods for adaptive Kalman filtering and smoothing are developed.…
Descriptors: Algorithms, Estimation (Mathematics), Mathematical Models, Maximum Likelihood Statistics

Davison, Mark L. – Psychometrika, 1976
Proposes a quadratic programming, least squares solution to Carroll's weighted unfolding model with nonnegativity constraints imposed on weights. It can be used to test various hypotheses about the weighted unfolding model with or without constraints. (RC)
Descriptors: Algorithms, Correlation, Goodness of Fit, Hypothesis Testing
Burtnyk, W. A. – 1972
This paper describes the method used by Tracz and Burtnyk for the estimation of future salary schedules in the Ontario secondary school system. The application of the algorithm to the Ontario secondary school system predicts a possible breakdown in the fixed step salary schedule at about 1980. This situation results primarily because of the…
Descriptors: Algorithms, Costs, Educational Planning, Mathematical Applications
Mislevy, Robert J. – 1985
A method for drawing inferences from complex samples is based on Rubin's approach to missing data in survey research. Standard procedures for drawing such inferences do not apply when the variables of interest are not observed directly, but must be inferred from secondary random variables which depend on the variables of interest stochastically.…
Descriptors: Algorithms, Data Interpretation, Estimation (Mathematics), Latent Trait Theory