Arrow Education reçoit la certification QUALIOPI
La certification QUALIOPI permet à nos clients de faire financer les formations de leurs collaborateurs par les organismes financeurs.
CODE: 0G51BG
DURÉE: 14 Hours (2 Jours)
PRIX H.T.: €1 490,00
This course provides an application-oriented introduction to the statistical component of IBM SPSS Statistics. Students will review several statistical techniques and discuss situations in which they would use each technique, how to set up the analysis, and how to interpret the results. This includes a broad range of techniques for exploring and summarizing data, as well as investigating and testing relationships. Students will gain an understanding of when and why to use these various techniques and how to apply them with confidence, interpret their output, and graphically display the results.
Introduction to statistical analysis
Describing individual variables
Testing hypotheses
Testing hypotheses on individual variables
Testing on the relationship between categorical variables
Testing on the difference between two group means
Testing on differences between more than two group means
Testing on the relationship between scale variables
Predicting a scale variable: Regression
Introduction to Bayesian statistics
Overview of multivariate procedures
IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS Statistics Base. Anyone who wants to refresh their knowledge and statistical experience.
Experience with IBM SPSS Statistics (version 18 or later), or Completion of the IBM SPSS Statistics Essentials course
Introduction to statistical analysis
Describing individual variables
Testing hypotheses
Testing hypotheses on individual variables
Testing on the relationship between categorical variables
Testing on the difference between two group means
Testing on differences between more than two group means
Testing on the relationship between scale variables
Predicting a scale variable: Regression
Introduction to Bayesian statistics
Overview of multivariate procedures