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. Less
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