Description
At Sixe Engineering we have been providing official IBM training around the world for over 12 years. Get the best training from our specialists in Europe. We have important discounts and offers for two or more students.
Course details
| IBM course code: 0G09BG | Category: IBM SPSS / SPSS Statistics |
| Delivery: Online & on-site** | Course length in days: 2 |
Target audience
IBM SPS Statistics users who want to learn advanced statistical methods to be able to better answer research questions.
Desired Prerequisites:
- Experience with IBM SPSS Statistics (version 18 or later)
- Knowledge of statistics, either by on the job experience, intermediate-level statistics oriented courses, or completion of the Statistical Analysis Using IBM SPSS Statistics (V26) course.
Instructors
The great majority of the IBM courses we offer are taught directly by our engineers. This is the only way we can guarantee the highest quality. We complement all the training with our own materials and laboratories, based on our experience during the deployments, migrations and courses that we have carried out during all these years.
Added value
Our courses are deeply role oriented. To give an example, the needs for technology mastery are different for developer teams and for the people in charge of deploying and managing the underlying infrastructure. The level of previous experience is also important and we take it very seriously. That is why beyond (boring) commands and tasks, we focus on solving the problems that arise in the day to day of each team. Providing them with the knowledge, competencies and skills required for each project. In addition, our documentation is based on the latest version of each product.
Agenda and course syllabus
Introduction to advanced statistical analysis
• Taxonomy of models
• Overview of supervised models
• Overview of models to create natural groupings
Grouping variables with Factor Analysis and Principal Components Analysis
• Factor Analysis basics
• Principal Components basics
• Assumptions of Factor Analysis
• Key issues in Factor Analysis
• Use Factor and component scores
Grouping cases with Cluster Analysis
• Cluster Analysis basics
• Key issues in Cluster Analysis
• K-Means Cluster Analysis
• Assumptions of K-Means Cluster Analysis
• TwoStep Cluster Analysis
• Assumptions of TwoStep Cluster Analysis
Predicting categorical targets with Nearest Neighbor Analysis
• Nearest Neighbors Analysis basics
• Key issues in Nearest Neighbor Analysis
• Assess model fit
Predicting categorical targets with Discriminant Analysis
• Discriminant Analysis basics
• The Discriminant Analysis model
• Assumptions of Discriminant Analysis
• Validate the solution
Predicting categorical targets with Logistic Regression
• Binary Logistic Regression basics
• The Binary Logistic Regression model
• Multinomial Logistic Regression basics
• Assumptions of Logistic Regression procedures
• Test hypotheses
• ROC curves
Predicting categorical targets with Decision Trees
• Decision Trees basics
• Explore CHAID
• Explore C&RT
• Compare Decision Trees methods
Introduction to Survival Analysis
• Survival Analysis basics
• Kaplan-Meier Analysis
• Assumptions of Kaplan-Meier Analysis
• Cox Regression
• Assumptions of Cox Regression
Introduction to Generalized Linear Models
• Generalized Linear Models basics
• Available distributions
• Available link functions
Introduction to Linear Mixed Models
• Linear Mixed Models basics
• Hierarchical Linear Models
• Modeling strategy
• Assumptions of Linear Mixed Models
Do you need to adapt this syllabus to your needs? Are you interested in other courses? Ask us without obligation.
Locations for on-site delivery
- Austria: Vienna
- Belgium: Brussels, Ghent
- Denmark: Cophenhagen
- Estonia: Tallinn
- Finland: Helsinki
- France: Paris, Marseille, Lyon
- Germany: Berlin, Munich, Cologne, Hamburg
- Greece: Athens, Thessaloniki
- Italy: Rome
- Louxemburg: Louxembourg (city)
- Netherlands: Amsterdam
- Norway: Oslo
- Portugal: Lisbon, Braga, Porto, Coimbra
- Slovakia: Bratislava
- Slovenia: Bratislava
- Spain: Madrid, Sevilla, Valencia, Barcelona, Bilbao, Málaga
- Sweden: Stockholm
- Turkey: Ankara
- United Kingdom: London
