Statistical Analysis Using IBM SPSS Statistics (V26)

Statistical Analysis Using IBM SPSS Statistics (V26)

IBM Training for Statistical Analysis Using IBM SPSS Statistics (V26)

Skill Level: Intermediate

Modality:  CR – Classroom based Training or ILO – Instructor Led Online Class

Duration: 2 Day/s

Starting Price:  $ – 1,306

Overview:

In this course you will learn how to visualize, describe, and test relationships between variables, using IBM SPSS Statistics (V26).

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.


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Target Audience:

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..

Prerequisites:

Experience with IBM SPSS Statistics (version 18 or later), or  Completion of the IBM SPSS Statistics Essentials course.

Topic:

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

 

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IBM Training

Objective:

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

 

Category: Data, Analytics, and AI

 

Product Name:

IBM SPSS Statistics

 

Badge and Certification Info:

Badge Title: Statistical Analysis Using IBM SPSS Statistics (V26) – Code: 0G51BG

Badge ID: a9c81411-c9a8-4290-933e-26e243e7a62a

 

Brand: Analytics

 

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