Learn main forecasting models from basic to expert level through a practical course with R statistical software.

Learn forecasting models through a practical course with R statistical software using real world data. It explores main concepts from basic to expert level which can help you achieve better grades, develop your academic career, apply your knowledge at work or make business forecasting related decisions. All of this while exploring the wisdom of best academics and practitioners in the field.

Become a Forecasting Models Expert in this Practical Course with R

Read data files and perform statistical computing operations by inputting instructions from R script files on the RGui console.
Compute simple benchmarking methods such as random walk.
Recognize time series patterns with moving averages and exponential smoothing (ETS) methods.
Assess if time series is first order trend stationary or constant in its mean.
Estimate time series conditional mean with autoregressive integrated moving average (ARIMA) models.
Define models’ parameters and evaluate if forecasting errors are white noise.
Select best methods and models automatically by comparing information loss criteria.
Test methods and models’ forecasting accuracy by comparing their predicting capabilities.
Become a Forecasting Models Expert and Put Your Knowledge in Practice

Learning forecasting methods and models is indispensable for business or financial analysts in areas such as sales and financial forecasting, inventory optimization, demand and operations planning, and cash flow management. It is also essential for academic careers in data science, applied statistics, operations research, economics, econometrics and quantitative finance. And it is necessary for any business forecasting related decision.