Survival Analysis Using SPSS: Statistics and Theory

Survival Analysis is one of the most important statistical methods used in medical research, engineering, social sciences, public health, reliability testing, epidemiology, and time-to-event modeling. This course, Survival Analysis, provides a complete, step-by-step understanding of how to analyze time-dependent outcomes, interpret survival functions, compare groups, and build predictive survival models.

Designed for students, researchers, and professionals, this course takes you from the core foundations to practical hands-on interpretation—including Kaplan-Meier estimation, Cox Regression, censoring, hazard rates, and APA-style reporting. By the end, you will be fully prepared to conduct your own survival-based research or replicate real-world studies.

What This Course Covers?

Foundations of Survival Analysis

You will begin with essential conceptual building blocks:

• Introduction to Survival Analysis

• What Survival Analysis Is

• History of Survival Analysis

Core Concepts and Terminology

To build a strong theoretical understanding, the course explains:

• Time, Event, and Residual Life

• Hazard, Hazard Rate, and Survival Rate

• Conditional Probability in Survival Analysis

• Understanding Censored vs. Uncensored Data

• Mean Time Between Failures (MTBF) vs. Mean Time To Failure (MTTF)

Kaplan–Meier vs. Cox Regression

A critical part of the course explains:

• When to use Kaplan–Meier?

• When to use Cox Regression?

• Research examples illustrating both methods

Hands-On Preparation for Survival Analysis

You will gain step-by-step guidance on:

• Setting data for survival analysis

• Formulating research objectives and hypotheses

• Understanding input options for the Kaplan–Meier method

Interpreting Survival Output

You will learn to interpret all major survival analysis results:

• Case Processing Summary & Survival Tables

• Mean Survival, Median Survival, Percentiles

• Pairwise Comparisons between groups

• Survival Function Plots

• Linking Survival Functions with other statistical results

APA Style Reporting

You will learn how to write:

• Complete APA-style reports for Kaplan-Meier Survival Analysis

• Clear, publication-ready interpretations of survival curves and statistical tests

Practical Project

The course concludes with:

• A real-world project replicating an actual survival analysis study
  — putting all your knowledge into practice.

By the End of This Course, You Will Be Able To:

• Understand key concepts such as hazard rate, survival rate, censoring, and time-to-event outcomes

• Collect and prepare data for survival analysis

• Run Kaplan–Meier survival analysis and Cox proportional hazards regression

• Interpret survival curves, group comparisons, and statistical tables

• Know when to apply each method and why

• Produce APA-style written reports suitable for research or publication

• Conduct independent survival analysis projects with confidence

Who Should Enroll?

This course is ideal for:

• Medical and clinical researchers

• Biological and health sciences students

• Data analysts and statisticians

• Engineers working on reliability analysis

• Social science researchers

• Graduate students preparing thesis or dissertation analyses

• Anyone working with time-to-event, duration, or failure-time data