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Welcome to Correlational Analysis Using IBM SPSS Statistics, a comprehensive course designed to help you master one of the most widely used statistical techniques for measuring rel...
Introduction to Correlations Using SPSS
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₹850.00
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Course overview
Welcome to Correlational Analysis Using IBM SPSS Statistics, a comprehensive course designed to help you master one of the most widely used statistical techniques for measuring relationships between variables. Whether you are a student, researcher, academic, or data analyst, this course provides the conceptual knowledge and practical skills needed to perform and interpret various correlation analyses using IBM SPSS Statistics.
The course begins with the fundamentals of correlational analysis, explaining when and why different correlation techniques should be used. You will learn the concepts, assumptions, calculations, and interpretations of Pearson's Correlation, Spearman's Rank Order Correlation, Biserial Correlation, and Point-Biserial Correlation. Through step-by-step demonstrations in SPSS, practical examples, and real-world datasets, you will gain hands-on experience in conducting correlation analyses, interpreting outputs, testing hypotheses, and reporting results according to APA style.
By the end of this course, you will have the confidence to perform correlational analysis using IBM SPSS Statistics and apply these techniques effectively in academic research, dissertations, theses, and professional data analysis.
Learning Outcomes
Understand the concepts, assumptions, and applications of correlational analysis.
Perform and interpret Pearson's, Spearman's, Biserial, and Point-Biserial correlations using IBM SPSS Statistics.
Select the appropriate correlation technique for different types of research data.
Test research hypotheses and interpret correlation outputs accurately.
Report correlation analysis results in APA style and research-standard format.
What you walk away with
Every course adds to three macro skills. Log in to swap platform averages for your own numbers.
Curriculum
Each module pairs the hand calculation with the same analysis in Excel, SPSS, R and Python.
Instructor
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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This course is designed for learners who want a practical, guided path through Data Analysis and Research.
Understand the concepts, assumptions, and applications of correlational analysis. Perform and interpret Pearson's, Spearman's, Biserial, and Point-Biserial correlations using IBM SPSS Statistics. Select the appropriate correlation technique...
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2h 14m
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