test

Ends in:
test
Skip to content
Scholarsight
Exploratory Factor Analysis in SPSS cover
Data Analysis and Research

Exploratory Factor Analysis in SPSS

0 students
Last updated Jul 2026

Course Overview

About This Course

Welcome to Exploratory Factor Analysis (EFA) Using IBM SPSS Statistics, a comprehensive course designed to help you understand and apply one of the most powerful multivariate statistical techniques for identifying the underlying structure of data. Whether you are a student, researcher, academic, or data analyst, this course provides the theoretical foundation and practical skills required to perform Exploratory Factor Analysis (EFA) using IBM SPSS Statistics.


The course begins with the fundamentals of factor analysis, explaining its purpose, assumptions, and applications in scale development, questionnaire validation, and construct measurement. You will learn how to assess data suitability using Kaiser-Meyer-Olkin (KMO) and Bartlett's Test of Sphericity, extract factors using appropriate methods, interpret eigenvalues and scree plots, apply factor rotation techniques, interpret factor loadings, and determine the optimal factor structure. Through step-by-step demonstrations in SPSS and practical examples, you will gain hands-on experience in conducting exploratory factor analysis, validating measurement instruments, and reporting results according to accepted academic and research standards.


By the end of this course, you will have the confidence to perform Exploratory Factor Analysis using IBM SPSS Statistics and apply it effectively in academic research, dissertations, theses, psychometrics, market research, and professional data analysis.

Learning Outcomes

Understand the concepts, assumptions, and applications of Exploratory Factor Analysis.

Perform Exploratory Factor Analysis using IBM SPSS Statistics with confidence.

Evaluate data suitability using KMO, Bartlett's Test, and other factor analysis diagnostics.

Extract, rotate, and interpret factors to identify underlying constructs accurately.

Report factor analysis results in APA style and research-standard format.

Curriculum

5 Sections • 29 Lectures
What is Factor Analysis?
2:13
Understanding Latent Variables and Indicators
1:03
Sample Researches Using FA in Social Science & Engineering
5:55
Historical Origin of FA & Its Application in Test Construction
4:37
Exploratory Factor Analysis vs. Confirmatory Factor Analysis (EFA vs. CFA)
5:18
Setting Data for Factor Analysis
2:34
Understanding Selection Variable
2:51
Univariate Descriptives & Initial Solutions Descriptive
1:19
Correlation Matrix Coefficients, Significance, Determinant, KMO & Bartlett's Test
4:31
Understanding Inverse, Reproduced, Anti-Image
3:59
Principle Component Analysis
2:55
Principle Axis Factoring
1:40
Maximum Likelihood Estimation Method
0:49
Choosing Correlation vs. Covariance Matrix for Factor Analysis
5:54
Interpreting Correlation Matrix & Unrotated Factor Solution
7:30
Determining number of factors: Scree Plot vs. Kaiser's Eigen Value Criteria
8:14
Factor Rotation: What It Is and Why its Done?
6:28
Rotation Methods: Varimax, Quartimax, Equamax, Direct Oblimin, Promax
8:04
Calculating Factor Scores: Regression, Bartlett, Anderson-Rubin
3:48
Factor Score Coefficient Matrix
1:40
Missing Value Analysis: Listwise, Pairwise, Replace with Mean
2:49
Sort by Size & Suppressing Smaller Coefficients
6:16
Part 1: Identifying Dimensions of Personality - 1
14:21
Part 2: Identifying Dimensions of Personality - 2
15:33
Part 3: Identifying Dimensions of Personality- 3
5:32
Part 4: Factor Naming
13:30
Part 5: Reliability Analysis of Factors- 1
22:32
Part 6: Reliability Analysis of Factors- 2
8:54
Part 8: Presenting Results of FA in APA Style
8:54
Meet your instructors

Learn from Experts and Leaders

4.5
Rating
1
Reviews
4
Students
32
Courses

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.

More

Reviews

0.0

0 reviews

All Reviews

No reviews yet

Be the first to share your experience with this course!

Expand Your Knowledge

Related Courses

Course preview

Preview

Loading preview...

Preview Unavailable

Forgot?