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Meta Analysis Using SPSS cover
Data Analysis and Research

Meta Analysis Using SPSS

0 students
Last updated Jul 2026

Course Overview

About This Course

Welcome to Meta-Analysis Using IBM SPSS Statistics, a comprehensive course designed to help you master the principles and practice of Meta-Analysis, one of the most powerful techniques for synthesizing evidence from multiple research studies. Whether you are a student, researcher, healthcare professional, academic, or data analyst, this course provides the knowledge and practical skills required to conduct and interpret meta-analyses using IBM SPSS Statistics.


The course begins with the fundamentals of meta-analysis, explaining its purpose, methodology, and importance in systematic reviews and evidence-based research. You will learn how to calculate and interpret effect sizes, assess heterogeneity, evaluate publication bias, perform fixed-effect and random-effects meta-analysis, explore moderator analyses, and interpret the results. Through practical demonstrations and real-world datasets, you will gain hands-on experience in conducting meta-analysis, synthesizing research findings, and reporting results according to accepted academic standards.


By the end of this course, you will have the confidence to perform meta-analysis using IBM SPSS Statistics and apply these techniques in research, systematic reviews, dissertations, and scientific publications.

Learning Outcomes

Understand the principles, methodology, and applications of Meta-Analysis.

Conduct Meta-Analysis using IBM SPSS Statistics with confidence.

Assess effect sizes, heterogeneity, and publication bias accurately.

Interpret Meta-Analysis results to support evidence-based research and decision-making.

Present Meta-Analysis findings in a professional and research-standard format.

Curriculum

2 Sections • 8 Lectures
Introduction to Meta Analysis
1:24
What is Meta Analysis and Why You Should Know About It?
9:04
Relationship Between Systematic Review and Meta Analysis
3:42
Locating Meta Analysis in the Family of Other Research Techniques
6:36
Is Meta-Analysis is Better than Hypothesis Testing?
3:00
Outcome of Meta Analysis: Effect Size, Forest Plot, and Publication Bias
4:05
What is Effect Size?
4:26
Understanding and Calculation of Cohen's d
3:05

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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