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: SPVC – Self Paced Virtual Class

Duration: 2 Day/s

Starting Price: $ – 735

Overview:

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

Contains: PDF course guide, as well as a lab environment where students can work through demonstrations and exercises at their own pace. 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 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.

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

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:

Badge ID:

Brand: Analytics

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