Demand Forecasting: Methods & Cognitive Biases

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Covers count data models and Poisson regression, then transitions to univariate time series analysis for forecasting economic variables.

Explores models for prediction, collaborative Sales and Operations Planning, supply chain management, and inventory optimization.

Covers the analysis and modeling of univariate time series, focusing on stationarity, ARMA processes, and forecasting.

Explores binary choice models like probit and logit, as well as univariate time series analysis with ARIMA models for forecasting economic variables.

Explores methods for predicting electricity demand evolution and estimating consumption.

Covers the Obermeyer solution approach for production planning and the impact of early market information.

Explores ARMA models in time series analysis, covering model selection, forecasting, and precision assessment.

Explores error estimation in numerical integration and its applications in forecasting, emphasizing the Romberg method and Richardson extrapolation.

Delves into advanced concrete structure design, covering loads, slabs, beams, calculations, and corbel models.

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