Live Webinar – August 20th 2012, 12:00-1:00 PM EDT
Offered by ASPE (REP 2161) 1 Category A PDU – Free PDU
This is a 1 hour seminar and attendees will be awarded 1 PDU for participating
The expansion of the capabilities for efficient gathering data has provided the foundation for the expansion of the analysis of operational data to provide information in support of business decision making.
The growth of capabilities for efficiently gathering data and the advent of software tools for decision-making support have led businesses to demand the effective analysis of raw data to sustain or achieve a competitive advantage. That demand is driving the need for organizations to expand their internal capabilities to perform the required analysis of the raw data.
This web seminar introduces key topics in the application of probability theory and statistical analysis to extract valuable information from the transactional data to identify critical variables and to draw reliable conclusions to apply in decision making.
ASPE also covers the application of regression analysis to quantify the relationship among variables and address its value in explaining and predicting behavior.
The topic of predictive model is expanded to introduce the concept of time series analysis of historical data as the building block for creating forecasting models of future events and results.
Statistical measures are introduced to provide a measure of the quality of the predictive and regression models.
The last topic addresses the development of decision models to determine the needs for information and the application of quantitative models in addressing those needs.
Presenter: Juan Santa-Coloma Juan’s background includes the application of quantitative techniques in the development of models for support of business operations and decision making. Juan has also been responsible for the delivery of training programs and coaching support of clients in areas of business re-engineering, BPM and business change implementation.
Click to register for Introduction to Analytics