Predictive Analytics with SPSS: Analyze & Apply
By the end of this course, learners will be able to import and manage datasets in SPSS, apply descriptive statistics, analyze correlations, construct linear and multiple regression models, and interpret logistic and multinomial regression outputs. Through hands-on practice with real-world case studies—including heart pulse, copper expansion, energy consumption, and debt assessment—learners will evaluate predictors, interpret coefficients, and validate results.
This course is designed to build a step-by-step mastery of predictive analytics using SPSS, starting from data handling fundamentals to advanced regression modeling. Each module integrates theory with applied case studies, enabling learners to connect statistical concepts to practical decision-making.
What makes this course unique is its structured approach that combines clear explanations, SPSS demonstrations, and diverse datasets across health, psychology, and finance domains. Learners will gain not only technical proficiency in SPSS but also the confidence to apply predictive modeling techniques in real-world research, business, and academic contexts. Whether you are a student, researcher, or professional, this course equips you with the tools to transform raw data into actionable insights.
Watch on Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
Related AI Lessons
⚡
⚡
⚡
⚡
The ABCs of reading medical research and review papers these days
Medium · LLM
#1 DevLog Meta-research: I Got Tired of Tab Chaos While Reading Research Papers.
Dev.to AI
How to Set Up a Karpathy-Style Wiki for Your Research Field
Medium · AI
The Non-Optimality of Scientific Knowledge: Path Dependence, Lock-In, and The Local Minimum Trap
ArXiv cs.AI
🎓
Tutor Explanation
DeepCamp AI