Statistica Advanced Analytics (ANL2)
Target:
The aim of this product course is to familiarize students with the tools of the data analysis package Statistica, which are offered in the modules Higher Models and Multivariate Explorative Techniques. The participants get an overview of the most important procedures of these modules and learn how to control the result output with the corresponding dialog interfaces.
Target group:
This course is aimed at professionals in service or industrial companies who want to perform complex data analyses with the Statistica software.
Course contents:
This course explains how to perform selected linear and nonlinear estimation methods and classifications with Statistica Professional. The topics:
- General Linear Models (ALM)
- Stepwise regression and best subset regression
- Partial least squares regression (PLS)
- Nonlinear regression (Levenberg-Marquardt, Gauss-Newton)
- Main Component Analysis (PCA)
- General Discrimination Analytical Models (GDA)
- Cluster analysis (K-Means and agglomerative methods)
The training consists of a short explanation of the mentioned procedures and the independent training of the course participants in the context of exercises. Examples in our standard courses are generally understandable data sets from different application areas.
Prerequisites:
This course requires program knowledge from "Statistica Analytics" (ANL1). To fully benefit from the training, participants should be familiar with the basic operation of the Statistica software and have methodological knowledge of multivariate statistics.
Supplementary courses:
For participants without sufficient previous knowledge we offer our method courses "Introduction to Statistics" (STA1) and "Linear Models" (STA2) and the product course "Statistica Introduction" (STE). Additional courses such as "Efficient Data Management" (EDM) or "Big Data Analytics" (BDA) are suitable.
Duration: 2 days Time: 9:30 - 17:00 h
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