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Welcome to Logistic Regression Analysis Using IBM SPSS Statistics, a comprehensive course designed to help you understand and apply Logistic Regression, one of the most widely used...
Logistic Regression Using SPSS
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₹850.00
Lifetime access
Course overview
Welcome to Logistic Regression Analysis Using IBM SPSS Statistics, a comprehensive course designed to help you understand and apply Logistic Regression, one of the most widely used predictive modeling techniques in statistics, research, and data science. Whether you are a student, researcher, academic, or data analyst, this course provides the theoretical foundation and practical skills required to perform logistic regression with confidence using IBM SPSS Statistics.
The course begins with the fundamentals of logistic regression, explaining its purpose, assumptions, and applications when the dependent variable is categorical. You will learn how to prepare data, build logistic regression models in SPSS, interpret model coefficients, odds ratios, classification tables, goodness-of-fit statistics, and model diagnostics. Through step-by-step demonstrations and practical examples, you will gain hands-on experience in testing research hypotheses, making predictions, and reporting findings according to APA style.
By the end of this course, you will have the confidence to perform Logistic Regression Analysis using IBM SPSS Statistics and apply it effectively in academic research, dissertations, theses, business analytics, healthcare, social sciences, and professional data analysis.
Learning Outcomes
Understand the concepts, assumptions, and applications of Logistic Regression Analysis.
Perform Logistic Regression using IBM SPSS Statistics with confidence.
Interpret logistic regression outputs, odds ratios, and model fit statistics accurately.
Develop and test research hypotheses using logistic regression models.
Report logistic regression 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 Logistic Regression Analysis. Perform Logistic Regression using IBM SPSS Statistics with confidence. Interpret logistic regression outputs, odds ratios, and model fit statistics accu...
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This course includes
2h 57m
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