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.
Predictive Analytics with SPSS: Analyze & Apply
Gain insight into a topic and learn the fundamentals.
2 weeks to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Import and manage real-world datasets in SPSS effectively.
Apply descriptive, correlation, and regression analyses confidently.
Interpret logistic and multinomial regression outputs accurately.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Recently updated!
October 2025
Assessments
22 assignments
Taught in English
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There are 6 modules in this course
This module introduces learners to importing data into SPSS, navigating software menus, and applying basic statistical concepts such as mean and standard deviation. Learners will also practice handling different data formats and explore essential data management tasks within SPSS.
What's included
9 videos3 assignments
This module focuses on correlation analysis and data visualization techniques. Learners will explore scatter plots, SPSS data editor tools, and real-world case studies to understand relationships between variables.
What's included
11 videos3 assignments
This module builds foundational knowledge of linear regression, from simple equations to real-world applications. Learners will study regression coefficients, interpret model outputs, and apply regression in diverse case studies such as copper expansion and energy consumption.
What's included
16 videos4 assignments
This module covers multiple regression and its applications in financial and health datasets. Learners will refine regression models, calculate predicted values, and explore case studies involving debt assessment and credit card data.
What's included
17 videos4 assignments
This module introduces advanced regression interpretation and logistic regression concepts. Learners will explore logistic regression case studies, define variables correctly in SPSS, and understand outputs such as coefficients and odds ratios.
What's included
16 videos4 assignments
This module explores multinomial regression, advanced interpretation of regression outputs, and case-based applications. Learners will practice interpreting outputs like case processing summaries, model fitting, and parameter estimates to draw meaningful conclusions.
What's included
17 videos4 assignments
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