# Statistical Analysis Using IBM SPSS Statistics (V26)

Durée:

2

Langue:

de

Prix:
1583.6
Description:

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.

â¢ Introduction to statistical analysisÂ
â¢ Describing individual variablesÂ
â¢ Testing hypothesesÂ
â¢ Testing hypotheses on individual variablesÂ
â¢ Testing on the relationship between categorical variablesÂ
â¢ Testing on the difference between two group meansÂ
â¢ Testing on differences between more than two group meansÂ
â¢ Testing on the relationship between scale variablesÂ
â¢ Predicting a scale variable: RegressionÂ
â¢ Introduction to Bayesian statisticsÂ
â¢ Overview of multivariate procedures

â¢ IBM SPSS Statistics users who want to familiarize themselves with the statistical capabilities of IBM SPSS Statistics Base.Â
â¢ Anyone who wants to refresh their knowledge and statistical experience.

â¢ Experience with IBM SPSS Statistics (version 18 or later), or Â
â¢ Completion of the IBM SPSS Statistics Essentials course

Introduction to statistical analysisÂ
â¢ Identify the steps in the research processÂ
â¢ Identify measurement levelsÂ

Describing individual variablesÂ
â¢ Chart individual variablesÂ
â¢ Summarize individual variablesÂ
â¢ Identify the normal distributionÂ
â¢ Identify standardized scoresÂ

Testing hypothesesÂ
â¢ Principles of statistical testingÂ
â¢ One-sided versus two-sided testingÂ
â¢ Type I, type II errors and powerÂ

Testing hypotheses on individual variablesÂ
â¢ Identify population parameters and sample statisticsÂ
â¢ Examine the distribution of the sample meanÂ
â¢ Test a hypothesis on the population meanÂ
â¢ Construct confidence intervalsÂ
â¢ Tests on a single variableÂ

Testing on the relationship between categorical variablesÂ
â¢ Chart the relationshipÂ
â¢ Describe the relationshipÂ
â¢ Test the hypothesis of independenceÂ
â¢ AssumptionsÂ
â¢ Identify differences between the groupsÂ
â¢ Measure the strength of the associationÂ

Testing on the difference between two group meansÂ
â¢ Chart the relationshipÂ
â¢ Describe the relationshipÂ
â¢ Test the hypothesis of two equal group meansÂ
â¢ AssumptionsÂ

Testing on differences between more than two group meansÂ
â¢ Chart the relationshipÂ
â¢ Describe the relationshipÂ
â¢ Test the hypothesis of all group means being equalÂ
â¢ AssumptionsÂ
â¢ Identify differences between the group meansÂ

Testing on the relationship between scale variablesÂ
â¢ Chart the relationshipÂ
â¢ Describe the relationshipÂ
â¢ Test the hypothesis of independenceÂ
â¢ AssumptionsÂ
â¢ Treatment of missing valuesÂ

Predicting a scale variable: RegressionÂ
â¢ Explain linear regressionÂ
â¢ Identify unstandardized and standardized coefficientsÂ
â¢ Assess the fitÂ
â¢ Examine residualsÂ
â¢ Include 0-1 independent variablesÂ
â¢ Include categorical independent variablesÂ

Introduction to Bayesian statisticsÂ
â¢ Bayesian statistics and classical test theoryÂ
â¢ The Bayesian approachÂ
â¢ Evaluate a null hypothesisÂ
â¢ Overview of Bayesian procedures in IBM SPSS StatisticsÂ

Overview of multivariate proceduresÂ
â¢ Overview of supervised modelsÂ
â¢ Overview of models to create natural groupings