John Fox s A Mathematical Primer for Social Statistics covers
many often ignored yet important topics in mathematics and
mathematical statistics. This text provides readers with the
foundation on which an understanding of applied statistics
rests.
Key Features
- Covers matrices, linear algebra, and vector geometry
. Discusses basic differential and integral calculus
. Focuses on probability and statistical estimation
. Develops by way of illustration the seminal statistical method
of linear least-squares regression
Intended Audience
This book is ideal for advanced undergraduates, graduate
students, and researchers in the social sciences who need to
understand and use relatively advanced statistical methods but
whose mathematical preparation for this work is insufficient.
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