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Multivariate Analysis of Variance (MANOVA) in SPSS cover
Data Analysis and Research

Multivariate Analysis of Variance (MANOVA) in SPSS

3 students
Last updated May 2026

About This Course

Course Description

This course offers a fundamental introduction to the MANOVA or Multivariate Analysis of Variance using SPSS. The course provides a focused explanation of MANOVA basics and understanding input options of MANOVA in SPSS.

 

Learning Outcomes

On completion of this course you will be able to:

  • Analyse data using MANOVA with confidence
  • Perform MANOVA in SPSS
  • Plan and test hypotheses based on MANOVA
  • Perform analysis based on MANOVA accurately and present the results in standard format.

Curriculum

2 Sections • 24 Lectures
Introduction to MANOVA
1:44
When to Use MANOVA?
4:22
Multivariate Test Decision Tree: When to Use ANOVA, MANOVA, ANCOVA, MANCOVA?
6:33
Assumptions of MANOVA
2:18
Research Questions and Study Design
9:07
Hypotheses Development
3:39
Dataset and Resources
0:08
Understanding MANOVA Window in SPSS
5:08
Specifying Model Full Factorial, Build Terms, and Custom Terms
4:14
Understanding Model Sum of Squares
5:56
What is Contrast?
2:18
Understanding Simple Contrast
2:08
Understanding Repeated Contrast
0:52
Understanding Polynomial Contrast
1:23
Understanding Deviation Contrast
1:40
Difference and Helmert Contrast
1:45
Understanding Estimated Marginal Means
3:24
Understanding SAVE Option
1:34
Understanding Parameter Estimates
0:46
Understanding SSCP Matrix and Residual SSCP Matrix
11:39
Understanding Transformation Matrix and Homogeneity Test
4:15
Understanding Spread and Residual Plots
1:17
Understanding Lack of Fit Test
1:14
Understanding General Estimable Function
0:35

Degree Track Only

This course is available inside a Degree Track and cannot be purchased separately.

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An experienced and passionate instructor, [Name] is dedicated to fostering a dynamic and engaging learning environment where students feel motivated to grow both academically and personally. With a strong foundation in their subject area, they bring clarity, structure, and enthusiasm to every lesson, ensuring complex concepts are made accessible and relevant. Their teaching approach blends theoretical knowledge with practical application, encouraging students to think critically and develop problem-solving skills. Known for their supportive and approachable demeanor, [Name] builds meaningful connections with students, understanding that each learner has unique strengths and challenges. They are committed to creating an inclusive classroom atmosphere where curiosity is encouraged, questions are welcomed, and every student feels valued. By adapting teaching methods to suit diverse learning styles, they help students gain confidence and achieve their full potential. Beyond the classroom, [Name] is deeply invested in continuous learning and professional development, staying updated with the latest educational practices and advancements in their field. They often contribute to curriculum development, mentorship programs, and extracurricular activities, reinforcing their role as not just an instructor, but a mentor and guide. Their ultimate goal is to inspire lifelong learning and empower students to succeed in an ever-evolving world.

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