May 1, 2024
Updated May 11, 2025
29 minute read
Discriminant Analysis is a powerful statistical method primarily used to classify observations into predefined groups or categories. Think of it as a way to find the mathematical rule that best distinguishes between different groups based on a set of characteristics or predictor variables. This technique is widely applied across various fields, from finance and marketing to biology and medicine, helping researchers and practitioners understand what makes groups distinct and predict which group a new observation is most likely to belong to.
b9c600|
Find a path to becoming a Discriminant Analysis. Learn more at:
OpenCourser.com/topic/b9c600/discriminant
Reading list
We've selected six books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Discriminant Analysis.
This classic textbook provides a comprehensive overview of discriminant analysis, covering both theoretical and practical aspects. It is suitable for advanced undergraduate and graduate students, as well as researchers and practitioners.
This introductory textbook provides a clear and concise overview of discriminant analysis. It is suitable for undergraduate students and practitioners with limited statistical background.
French-language textbook on discriminant analysis. It is suitable for advanced undergraduate and graduate students, as well as researchers and practitioners.
Provides a comprehensive overview of discriminant analysis in finance. It is suitable for practitioners and researchers with some statistical background.
Provides a comprehensive overview of discriminant analysis in healthcare. It is suitable for practitioners and researchers with some statistical background.
Provides a comprehensive overview of discriminant analysis in biomedical research.
For more information about how these books relate to this course, visit:
OpenCourser.com/topic/b9c600/discriminant