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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, 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.
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What You'll Learn

  • 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

Who Should Attend

  • 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.
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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.

Learning Journey

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1. Introduction to statistical analysis

  • Identify the steps in the research process
  • Principles of statistical analysis

2. Examine individual variables

  • Identify measurement levels
  • Chart individual variables
  • Summarize individual variables
  • Examine the normal distribution
  • Examine standardized scores

3. Test 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 Test

4. Test 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 association

5. Test 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 Test

6. Test 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 tests

7. Test 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 values

8. Predict 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 variables

9. Introduction 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

10. Overview of multivariate procedures

  • Overview of supervised models
  • Overview of models to create natural grouping

This course is not associated with any Certification.

Frequently Asked Questions (FAQs)

  • Why get IBM certified?

    IBM certifications validate your skills and expertise in a wide range of technologies, including hybrid cloud, data & AI, security, IT infrastructure, and business applications.

    These certifications are globally recognized and can help you advance your career, increase your earning potential, and demonstrate your commitment to professional development.

    IBM-certified professionals are in high demand, making them valuable assets to any organization seeking to leverage IBM's innovative solutions.

  • What to expect for the examination?

    IBM offers a variety of certification exams at different levels (Basic, Intermediate, and Advanced) covering various technologies and job roles.

    Exams typically consist of multiple-choice questions and may include scenario-based questions that assess your ability to apply your knowledge in real-world situations.

    Note: Certification requirements and policies may be updated by IBM from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • How long is IBM certification valid for?

    The validity period of IBM certifications varies. Some certifications, particularly those focused on specific product versions or technologies, may have expiration dates.

    However, many IBM certifications, especially those focused on broader skills or newer technologies, do not have an expiration date.

    Note: Certification requirements and policies may be updated by IBM from time to time. We apologize for any discrepancies; do get in touch with us if you have any questions.

  • Why take this course with Trainocate?

    Here’s what sets us apart:

    - Global Reach, Localized Accessibility: Benefit from our geographically diverse training hubs in 16 countries (and counting!).

    - Top-Rated Instructors: Our team of subject matter experts (with high average CSAT and MTM scores) are passionate to help you accelerate your digital transformation.

    - Customized Training Solutions: Choose from on-site, virtual classrooms, or self-paced learning to fit your organization and individual needs.

    - Experiential Learning: Dive into interactive training with our curated lesson plans. Participate in hands-on labs, solve real-world challenges, and take on comprehensive assessments.

    - Learn From The Best: With 30+ authorized training partnerships and countless awards from Microsoft, AWS, Google – you're guaranteed learning from the industry's elite.

    - Your Bridge To Success: We provide up-to-date course materials, helpful exam guides, and dedicated support to validate your expertise and elevate your career.

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