Learners will be able to analyze complex datasets, interpret advanced statistical outputs, and apply predictive modeling techniques using SPSS 2024. By the end of this course, learners will confidently evaluate relationships between variables, build and interpret regression models, and translate statistical results into actionable insights for business and healthcare contexts. This course is designed to take learners beyond basic SPSS usage into advanced analytical thinking. Through real-world case studies—including market analysis, finance, home loans, and healthcare datasets—learners will apply descriptive analytics, correlation analysis, linear and multiple regression, logistic regression, and quadratic regression techniques. Each concept is reinforced with visual diagnostics such as scatter plots and residual analysis to ensure robust interpretation and model validation. What makes this course unique is its strong emphasis on interpretation over computation. Rather than focusing solely on running SPSS commands, the course trains learners to understand why results occur and how to communicate insights effectively. The inclusion of end-to-end data preparation using both Excel and SPSS further ensures learners are industry-ready. This course is ideal for students, analysts, and professionals who want to strengthen their data-driven decision-making skills using SPSS in practical, real-world scenarios.
What you'll learn
analyze complex datasets
interpret advanced statistical outputs
apply predictive modeling techniques using SPSS
build and interpret regression models
translate statistical results into actionable insights
conduct descriptive analytics and correlation analysis
use linear, multiple, logistic, and quadratic regression techniques
Course objectives
to enable confident evaluation of relationships between variables
to prepare learners for industry-ready data preparation using Excel and SPSS
to reinforce concepts through visual diagnostics like scatter plots and residual analysis