Statistical Analysis Using IBM SPSS Statistics (V25)

Course code

0G51AUA

Duration

2 Days, 16 Acad. Hours

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Course Overview

Objectives

Prerequisites

Course Outline

Course Overview

Course overivew

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, as well as 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 as well as how to apply them with confidence, interpret their output, and graphically display the results.

Objectives

Course objectives

Introduction to statistical analysis
Examine individual variables
Test hypotheses about individual variables
Test the relationship between categorical variables
Test on the difference between two group means
Test on differences between more than two group means
Test the relationship between scale variables
Predict a scale variable: Regression
Introduction to Bayesian statistics
Overview of multivariate procedures

Prerequisites

Audience

Anyone who has worked with IBM SPSS Statistics and wants to become better versed in the basic statistical capabilities of IBM SPSS Statistics Base.
Anyone who wants to refresh their knowledge and statistical experience.

Prerequisites

Familiarity with basic concepts in statistics, such as measurement levels, mean, and standard deviation.
Familiarity with the windows in IBM SPSS Statistics either by experience with IBM SPSS Statistics (version 18 or later) or completion of the IBM SPSS Statistics Essentials (V25) course.

Course Outline

Course topics

1. Introduction to statistical analysis

Identify the steps in the research process
Principles of statistical analysisExamine individual variables
Identify measurement levels
Chart individual variables
Summarize individual variables
Examine the normal distribution
Examine standardized scoresTest hypotheses about individual variables
Identify population parameters and sample statistics
Examine the distribution of the sample mean
Determine the sample size
Test a hypothesis on the population mean
Construct a confidence interval for the population mean
Tests on a single variable: One-Sample T Test, Paired-Samples T Test, and Binomial TestTest the relationship between categorical variables
Chart the relationship between two categorical variables
Describe the relationship: Compare percentages in Crosstabs
Test the relationship: The Chi-Square test in Crosstabs
Assumptions of the Chi-Square test
Pairwise compare column proportions
Measure the strength of the associationTest on the difference between two group means
Compare the Independent-Samples T Test to the Paired-Samples T Test
Chart the relationship between the group variable and scale variable
Describe the relationship: Compare group means
Test on the difference between two group means: Independent-Samples T Test
Assumptions of the Independent-Samples T TestTest on differences between more than two group means
Describe the relationship: Compare group means
Test the hypothesis of equal group means: One-Way ANOVA
Assumptions of One-Way ANOVA
Identify differences between group means: Post-hoc testsTest the relationship between scale variables
Chart the relationship between two scale variables
Describe the relationship: Correlation
Test on the correlation
Assumptions for testing on the correlation
Treatment of missing valuesPredict a scale variable: Regression
What is linear regression?
Explain unstandardized and standardized coefficients
Assess the fit of the model: R Square
Examine residuals
Include 0-1 independent variables
Include categorical independent variablesIntroduction to Bayesian statistics
Bayesian statistics versus classical test theory
Explain the Bayesian approach
Evaluate a null hypothesis: Bayes Factor
Bayesian procedures in IBM SPSS Statistics

2. Overview of multivariate procedures

Overview of supervised models
Overview of models to create natural groupings

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Statistical Analysis Using IBM SPSS Statistics (V25)

Course code:

0G51AUA

Duration:

2 Days, 16 Acad. Hours

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