Data Science / Statistics / IBM / SPSS / SPSS Statistics - Statistical Data Analysis 3 (Questionnaires, Surveys and Market Research)
| ID | 2858622 |
|---|---|
| Classroom | 3 days 9:00-16:30 |
| Webinar | 5 days 9:00-12:30 |
| Method | Presentation with examples and hands-on labs. |
| Prequisite | Basics in Statistics |
| Audience | Data Analysts |
IBM SPSS Direct Marketing helps you understand your customers in greater depth, improve your marketing campaigns and maximize the ROI of your marketing budget. This training shows you how to conduct sophisticated analyses of your customers or contacts – and with a high level of confidence in your results. You will get to know concepts like cluster analysis, prospect profiling, Conjoint Analysis, Multidimensional Scaling, Correspondence Analysis or the analysis of complex samples. For legal reasons (license management), this training can only be delivered on your hardware using your (test) license. Please contact us concerning dates and handling before the actual booking.
Crosstabs - Summarizing Values ??- OLAP Cubes - Sample t-Tests - Components of Variance - One-Way ANOVA - Custom Tables: Simple Tables for Categorical Variables, Stacking, Nesting, and Layers with Categorical Variables, Totals and Subtotals, Computed Categories
Generalized Linear Models - Generalized Linear Mixed Models - Model Loglinear Analysis - General Loglinear Analysis - Logit Loglinear Analysis
Categorical Regression: Define the Scale in the Categorical Regression, Discretization, Missing Values??, Output - Categorical Principal Components Analysis: Defining Scale and Weight, Discretization, Missing Values??, Output
Profile Method: Orthogonal Field, Experimental Stimuli, Data Collection and Analysis - Generating an Orthogonal Design - Display
Multidimensional Scaling Analysis of Similarities, Creating Distances from Data - Defining a Model for the Multidimensional Scaling - Multidimensional Unfolding: Defining a Model Output
Defining the Row and Column Range in the Correspondence Analysis - Model - Statistics - Charts - Multiple Correspondence Analysis: Definition of the Variables´ Weight in the Multiple Correspondence Analysis, Discretization, Missing Values??, Output, Diagrams
Stichprobenziehung mithilfe eines komplexen Plans - Vorbereiten einer komplexen Stichprobe für die Analyse - Häufigkeiten, Kreuztabellen und Deskriptive Statistiken - Regression für komplexe Stichproben: Logistische Regression, Ordinale Regression, Cox-Regression
RFM-Analyse - Clusteranalyse - Profile über potenzielle Kunden - Responseraten nach Postleitzahlen - Kaufneigung - Kontrollpakettest
Marco Skulschus (born in Germany in 1978) studied economics in Wuppertal (Germany) and Paris (France) and wrote his master´s thesis about semantic data modeling. He started working as a lecturer and consultant in 2002.
He works as an IT-consultant and project manager. He developed various Business Intelligence systems for industry clients and the public sector. For several years now, he is responsible for a BI-team in India which is mainly involved in BI and OLAP projects, reporting systems as well as statistical analysis and Data Mining.
He led several research projects and was leading scientist and project manager of a publicly funded project about interactive questionnaires and online surveys.
