Introduction to Measure and Integration

This paperback, gives a self-contained treatment of the theory of finite measures in general spaces at the undergraduate level.

This paperback, which comprises the first part of Introduction to Measure and Probability by J. F. C. Kingman and S. J. Taylor, gives a self-contained treatment of the theory of finite measures in general spaces at the undergraduate level. It sets the material out in a form which not only provides an introduction for intending specialists in measure theory but also meets the needs of students of probability. The theory of measure and integration is presented for general spaces, with Lebesgue measure and the Lebesgue integral considered as important examples whose special properties are obtained. The introduction to functional analysis which follows covers the material to probability theory and also the basic theory of L2-spaces, important in modern physics. A large number of examples is included; these form an essential part of the development.

Preface; 1. Theory of sets; 2. Point set topology; 3. Set functions; 4. Construction and properties of measure; 5. Definitions and properties of the integral; 6. Related Spaces and measures; 7. The space of measurable functions; 8. Linear functionals; 9. Structure of measures in special spaces; Index of notation; General index.

This paperback, which comprises the first part of Introduction to Measure and Probability by J. F. C. Kingman and S. J. Taylor, gives a self-contained treatment of the theory of finite measures in general spaces at the undergraduate level. It sets the material out in a form which not only provides an introduction for intending specialists in measure theory but also meets the needs of students of probability.