Developed for those following the Statistics 1 unit within the Mathematics and Applied Mathematics courses at Advanced Higher Level, this title is part of a series of five covering the Advanced Higher units in Mathematics and Statistics. All the books in the series pprovide: a straightforward route through the course with complete and ordered coverage of the units; numerous questions for practice and consolidation; thorough preparation for end-of-unit and end of course assessments.
This is a series of five books each covering a separate unit of the Advanced Higher course. This unit structure gives you the flexibility to put together a complete course or to offer separate units of study.
This is a series of five books each covering a separate unit of the Advanced Higher course. This unit structure gives you the flexibility to put together a complete course or to offer separate units of study.
This new book provides additional practice exercises matched precisely to the performance criteria for all four units of Higher Mathematics. It prepares students for internal Unit Tests and external Course Assessments in Mathematics and Statistics.
This is a series of five books each covering a separate unit of the Advanced Higher course. This unit structure gives you the flexibility to put together a complete course or to offer separate units of study.
This is a collection of the 2002-2005 official SQA past papers for Advanced Higher mathematics. A comprehensive answer section shows exactly what examiners are looking for and how to aim for the best grade.
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
An authorised reissue of the long out of print classic textbook, Advanced Calculus by the late Dr Lynn Loomis and Dr Shlomo Sternberg both of Harvard University has been a revered but hard to find textbook for the advanced calculus course for decades.This book is based on an honors course in advanced calculus that the authors gave in the 1960's. The foundational material, presented in the unstarred sections of Chapters 1 through 11, was normally covered, but different applications of this basic material were stressed from year to year, and the book therefore contains more material than was covered in any one year. It can accordingly be used (with omissions) as a text for a year's course in advanced calculus, or as a text for a three-semester introduction to analysis.The prerequisites are a good grounding in the calculus of one variable from a mathematically rigorous point of view, together with some acquaintance with linear algebra. The reader should be familiar with limit and continuity type arguments and have a certain amount of mathematical sophistication. As possible introductory texts, we mention Differential and Integral Calculus by R Courant, Calculus by T Apostol, Calculus by M Spivak, and Pure Mathematics by G Hardy. The reader should also have some experience with partial derivatives.In overall plan the book divides roughly into a first half which develops the calculus (principally the differential calculus) in the setting of normed vector spaces, and a second half which deals with the calculus of differentiable manifolds.
