Statistical Analysis Using IBM SPSS Statistics (V26) [TDS_0G51BG]

OVERVIEW

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.

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

OBJECTIVES

• 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

AUDIENCE

• IBM SPS 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.

CONTENT

Introduction to statistical analysis 
• Identify the steps in the research process 
• Identify measurement levels 

Describing individual variables 
• Chart individual variables 
• Summarize individual variables 
• Identify the normal distribution 
• Identify standardized scores 

Testing hypotheses 
• Principles of statistical testing 
• One-sided versus two-sided testing 
• Type I, type II errors and power 

Testing hypotheses on individual variables 
• Identify population parameters and sample statistics 
• Examine the distribution of the sample mean 
• Test a hypothesis on the population mean 
• Construct confidence intervals 
• Tests on a single variable 

Testing on the relationship between categorical variables 
• Chart the relationship 
• Describe the relationship 
• Test the hypothesis of independence 
• Assumptions 
• Identify differences between the groups 
• Measure the strength of the association 

Testing on the difference between two group means 
• Chart the relationship 
• Describe the relationship 
• Test the hypothesis of two equal group means 
• Assumptions 

Testing on differences between more than two group means 
• Chart the relationship 
• Describe the relationship 
• Test the hypothesis of all group means being equal 
• Assumptions 
• Identify differences between the group means 

Testing on the relationship between scale variables 
• Chart the relationship 
• Describe the relationship 
• Test the hypothesis of independence 
• Assumptions 
• Treatment of missing values 

Predicting a scale variable: Regression 
• Explain linear regression 
• Identify unstandardized and standardized coefficients 
• Assess the fit 
• Examine residuals 
• Include 0-1 independent variables 
• Include categorical independent variables 

Introduction to Bayesian statistics 
• Bayesian statistics and classical test theory 
• The Bayesian approach 
• Evaluate a null hypothesis 
• Overview of Bayesian procedures in IBM SPSS Statistics 

Overview of multivariate procedures 
• Overview of supervised models 
• Overview of models to create natural groupings