Foundations of Real and Abstract Analysis
The core of this book, Chapters 3 through 5, presents a course on metric, normed,andHilbertspacesatthesenior/graduatelevel. Themotivationfor each of these chapters is the generalisation of a particular attribute of the n Euclidean spaceR : in Chapter 3, that attribute isdistance; in Chapter 4, lengt...
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description | The core of this book, Chapters 3 through 5, presents a course on metric, normed,andHilbertspacesatthesenior/graduatelevel. Themotivationfor each of these chapters is the generalisation of a particular attribute of the n Euclidean spaceR : in Chapter 3, that attribute isdistance; in Chapter 4, length; and in Chapter 5, inner product. In addition to the standard topics that, arguably, should form part of the armoury of any graduate student in mathematics, physics, mathematical economics, theoretical statistics,. . . , this part of the book contains many results and exercises that are seldom found in texts on analysis at this level. Examples of the latter are Wong’s Theorem(3. 3. 12)showingthattheLebesguecoveringpropertyisequivalent to the uniform continuity property, and Motzkin’s result (5. 2. 2) that a nonempty closed subset of Euclidean space has the unique closest point property if and only if it is convex. The sad reality today is that, perceiving them as one of the harder parts oftheirmathematicalstudies,studentscontrivetoavoidanalysiscoursesat almost any cost, in particular that of their own educational and technical deprivation. Many universities have at times capitulated to the negative demand of students for analysis courses and have seriously watered down their expectations of students in that area. As a result, mathematics - jors are graduating, sometimes with high honours, with little exposure to anything but a rudimentary course or two on real and complex analysis, often without even an introduction to the Lebesgue integral. |
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Themotivationfor each of these chapters is the generalisation of a particular attribute of the n Euclidean spaceR : in Chapter 3, that attribute isdistance; in Chapter 4, length; and in Chapter 5, inner product. In addition to the standard topics that, arguably, should form part of the armoury of any graduate student in mathematics, physics, mathematical economics, theoretical statistics,. . . , this part of the book contains many results and exercises that are seldom found in texts on analysis at this level. Examples of the latter are Wong’s Theorem(3. 3. 12)showingthattheLebesguecoveringpropertyisequivalent to the uniform continuity property, and Motzkin’s result (5. 2. 2) that a nonempty closed subset of Euclidean space has the unique closest point property if and only if it is convex. The sad reality today is that, perceiving them as one of the harder parts oftheirmathematicalstudies,studentscontrivetoavoidanalysiscoursesat almost any cost, in particular that of their own educational and technical deprivation. Many universities have at times capitulated to the negative demand of students for analysis courses and have seriously watered down their expectations of students in that area. 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The sad reality today is that, perceiving them as one of the harder parts oftheirmathematicalstudies,studentscontrivetoavoidanalysiscoursesat almost any cost, in particular that of their own educational and technical deprivation. Many universities have at times capitulated to the negative demand of students for analysis courses and have seriously watered down their expectations of students in that area. As a result, mathematics - jors are graduating, sometimes with high honours, with little exposure to anything but a rudimentary course or two on real and complex analysis, often without even an introduction to the Lebesgue integral.</description><subject>Mathematical analysis</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Mathematics. 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Analysis</topic><topic>Operations research</topic><topic>Operations Research/Decision Theory</topic><topic>Real Functions</topic><toplevel>online_resources</toplevel><creatorcontrib>Bridges, Douglas S</creatorcontrib><creatorcontrib>SpringerLink (Online service)</creatorcontrib><collection>Casalini Torrossa eBook Single Purchase</collection><collection>National Library of New Zealand Catalogue</collection><collection>National Bibliographic Database</collection><collection>Publications New Zealand</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bridges, Douglas S</au><aucorp>SpringerLink (Online service)</aucorp><format>book</format><genre>book</genre><ristype>BOOK</ristype><btitle>Foundations of Real and Abstract Analysis</btitle><seriestitle>Graduate Texts in Mathematics</seriestitle><date>2006</date><risdate>2006</risdate><volume>174</volume><issn>0072-5285</issn><isbn>0387226206</isbn><isbn>9780387226200</isbn><isbn>9780387982397</isbn><isbn>0387982396</isbn><isbn>1475771614</isbn><isbn>9781475771602</isbn><isbn>1475771606</isbn><isbn>9781475771619</isbn><eisbn>0387226206</eisbn><eisbn>9780387226200</eisbn><abstract>The core of this book, Chapters 3 through 5, presents a course on metric, normed,andHilbertspacesatthesenior/graduatelevel. 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subjects | Mathematical analysis Mathematics Mathematics and Statistics Mathematics. Analysis Operations research Operations Research/Decision Theory Real Functions |
title | Foundations of Real and Abstract Analysis |
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