Analyze Financial & Market Data Using SPSS Regression

Overview

Learners will analyze real-world financial and equity market datasets, apply simple and multiple regression techniques in SPSS, interpret statistical outputs, and evaluate model validity using visual diagnostics. By the end of this course, learners will be able to translate regression results into actionable insights and confidently communicate analytical findings. This hands-on course is designed for learners who want to move beyond theory and gain practical experience through three applied SPSS projects covering home loan analysis and equity market data. Learners begin with foundational regression concepts using familiar financial variables, then progressively advance to complex market-based multiple regression models. Each project emphasizes correct model setup, coefficient estimation, statistical significance, and result interpretation supported by scatter plot visualization. What makes this course unique is its project-driven structure, which mirrors real-world data analytics workflows used in finance and market research. Instead of isolated examples, learners work with end-to-end regression cases, reinforcing analytical thinking and decision-making skills. Completing this course equips learners with job-ready SPSS regression expertise applicable to finance, analytics, and business intelligence roles.

Syllabus

Regression Foundations Using SPSS Projects

This module introduces learners to applied regression analysis using SPSS through real-world financial and market data projects. Learners develop foundational skills in project setup, data preparation, regression estimation, result interpretation, and visual diagnostics to support evidence-based decision-making.

Advanced Market Regression and Visualization

This module advances learners’ regression expertise by applying multiple regression techniques to complex equity market datasets. Learners focus on extended coefficient analysis, deep interpretation of multivariable models, and advanced visualization methods to validate and communicate analytical findings.