What you'll get
  • 2+ Hours
  • 1 Courses
  • Course Completion Certificates
  • Self-paced Courses
  • Technical Support
  • Case Studies

Synopsis

  • Covers the theoretical foundations of logistic regression analysis.
  • Provides practical implementation using IBM SPSS Statistics Data Editor and Viewer.
  • Demonstrates application of logistic regression techniques using MS Excel.
  • Guides learners in interpreting variable equations and analyzing model outputs.
  • Offers hands-on experience with real-world datasets, such as smoke preferences and heart pulse studies.
  • Teaches effective generation and interpretation of output results.
  • Explains techniques for assessing model fit, validity, and troubleshooting common analysis issues.
  • Utilizes practice files to reinforce concepts and enhance proficiency.
  • Equips learners with mastery of logistic regression for informed decision-making in research and data analysis.
  • Enhances predictive modeling skills applicable across various business sectors.
  • Includes practical datasets for predictive analysis with step-by-step observation, interpretation, prediction, and conclusion.
  • Covers higher-order regression models, including quadratic and polynomial regressions.

Content

Courses No. of Hours Certificates Details
SPSS:05 - Logistic Regression2h 37m✔View Curriculum

Description

This comprehensive course guides participants through mastering logistic regression analysis. It begins with a detailed exploration of logistic regression concepts, ensuring a solid understanding of theoretical foundations before moving to practical application using IBM SPSS Statistics Data Editor and Viewer.

Learners gain hands-on experience applying logistic regression techniques in MS Excel through real-world examples, such as studies on smoke preferences and heart pulse data. Participants explore variables, generate output, and interpret results, developing insights into applying logistic regression across diverse scenarios.

The course includes practice files with datasets and exercises, allowing participants to reinforce concepts and build practical proficiency. Expert guidance throughout ensures learners become confident in using both IBM SPSS and MS Excel for data analysis.

By the end of the training, participants can apply logistic regression techniques to their projects and research, confidently making data-driven decisions.

Requirements

  • Familiarity with quantitative methods
  • Basic knowledge of MS Office
  • Experience with Paint or similar tools for data visualization

Target Audience

  • Data Engineers
  • Data Analysts
  • Data Architects
  • Software Engineers
  • IT Operations Professionals
  • Technical Managers