This book PDF is perfect for those who love Social Science genre, written by John Fox and published by SAGE which was released on 26 April 2024 with total hardcover pages 185. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related A Mathematical Primer for Social Statistics books below.
| Author | : John Fox |
| File Size | : 42,8 Mb |
| Publisher | : SAGE |
| Language | : English |
| Release Date | : 26 April 2024 |
| ISBN | : 9781412960809 |
| Pages | : 185 pages |
The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods
The ideal primer for students and researchers across the social sciences who wish to master the necessary maths in order to pursue studies involving advanced statistical methods
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A Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based
Get BookA Mathematical Primer for Social Statistics, Second Edition presents mathematics central to learning and understanding statistical methods beyond the introductory level: the basic "language" of matrices and linear algebra and its visual representation, vector geometry; differential and integral calculus; probability theory; common probability distributions; statistical estimation and inference, including likelihood-based
Get BookThis book will be of interest to anyone who wishes to know what role mathematics can play in attempting to comprehend the dynamics of the human brain. It also aims to serve as a general introduction to neuromathematics. The book gives the reader a qualitative understanding and working knowledge of
Get BookCombining a modern, data-analytic perspective with a focus on applications in the social sciences, the Third Edition of Applied Regression Analysis and Generalized Linear Models provides in-depth coverage of regression analysis, generalized linear models, and closely related methods, such as bootstrapping and missing data. Updated throughout, this Third Edition includes
Get BookOriginally published in 1982, this book describes those basic ideas and techniques of statistics which should be known to every social scientist. The explanations are given in careful detail at a level of mathematical sophistication which will be readily attainable by students meeting statistical methods for the first time. All the
Get BookStatistical methods in modern research increasingly entail developing, estimating and testing models for data. Rather than rigid methods of data analysis, the need today is for more flexible methods for modelling data. In this logical, easy-to-follow and exceptionally clear book, David Flora provides a comprehensive survey of the major statistical
Get BookSimply put, Thinking Through Statistics is a primer on how to maintain rigorous data standards in social science work, and one that makes a strong case for revising the way that we try to use statistics to support our theories. But don’t let that daunt you. With clever examples
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