Real Analysis Chapter 1 Solutions Jonathan Conder

Similar documents
Lebesgue Measure. Dung Le 1

II - REAL ANALYSIS. This property gives us a way to extend the notion of content to finite unions of rectangles: we define

Chapter 4. Measure Theory. 1. Measure Spaces

The Caratheodory Construction of Measures

Measures and Measure Spaces

1.4 Outer measures 10 CHAPTER 1. MEASURE

Measure and Integration: Concepts, Examples and Exercises. INDER K. RANA Indian Institute of Technology Bombay India

Real Analysis Chapter 3 Solutions Jonathan Conder. ν(f n ) = lim

MATH5011 Real Analysis I. Exercise 1 Suggested Solution

Indeed, if we want m to be compatible with taking limits, it should be countably additive, meaning that ( )

MATH41011/MATH61011: FOURIER SERIES AND LEBESGUE INTEGRATION. Extra Reading Material for Level 4 and Level 6

Chapter 1. Measure Spaces. 1.1 Algebras and σ algebras of sets Notation and preliminaries

Partial Solutions to Folland s Real Analysis: Part I

Measures. Chapter Some prerequisites. 1.2 Introduction

MATHS 730 FC Lecture Notes March 5, Introduction

DRAFT MAA6616 COURSE NOTES FALL 2015

Integration on Measure Spaces

Existence of a Limit on a Dense Set, and. Construction of Continuous Functions on Special Sets

Lecture 3: Probability Measures - 2

FUNDAMENTALS OF REAL ANALYSIS by. II.1. Prelude. Recall that the Riemann integral of a real-valued function f on an interval [a, b] is defined as

Problem set 1, Real Analysis I, Spring, 2015.

Construction of a general measure structure

Measure on the Real Line

INTRODUCTION TO MEASURE THEORY AND LEBESGUE INTEGRATION

1.1. MEASURES AND INTEGRALS

arxiv: v1 [math.fa] 14 Jul 2018

3 (Due ). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure?

+ = x. ± if x > 0. if x < 0, x

Dual Space of L 1. C = {E P(I) : one of E or I \ E is countable}.

Daniel Akech Thiong Math 501: Real Analysis Homework Problems with Solutions Fall Problem. 1 Give an example of a mapping f : X Y such that

MAT1000 ASSIGNMENT 1. a k 3 k. x =

Lebesgue measure and integration

Real Analysis Chapter 4 Solutions Jonathan Conder

Lebesgue Measure on R n

Real Variables: Solutions to Homework 3

Measure Theoretic Probability. P.J.C. Spreij

Lebesgue Measure on R n

Moreover, µ is monotone, that is for any A B which are both elements of A we have

G1CMIN Measure and Integration

1/12/05: sec 3.1 and my article: How good is the Lebesgue measure?, Math. Intelligencer 11(2) (1989),

Measurable functions are approximately nice, even if look terrible.

HW 4 SOLUTIONS. , x + x x 1 ) 2

Chapter 8. General Countably Additive Set Functions. 8.1 Hahn Decomposition Theorem

Review of measure theory

Lebesgue measure on R is just one of many important measures in mathematics. In these notes we introduce the general framework for measures.

Measure and integration

Measure Theory & Integration

Measure Theory. John K. Hunter. Department of Mathematics, University of California at Davis

n [ F (b j ) F (a j ) ], n j=1(a j, b j ] E (4.1)

Math 4121 Spring 2012 Weaver. Measure Theory. 1. σ-algebras

REAL ANALYSIS LECTURE NOTES: 1.4 OUTER MEASURE

THEOREMS, ETC., FOR MATH 515

The Lebesgue Integral

Chapter 5. Measurable Functions

l(y j ) = 0 for all y j (1)

(2) E M = E C = X\E M

Measures. 1 Introduction. These preliminary lecture notes are partly based on textbooks by Athreya and Lahiri, Capinski and Kopp, and Folland.

13. Examples of measure-preserving tranformations: rotations of a torus, the doubling map

Differentiation of Measures and Functions

MATS113 ADVANCED MEASURE THEORY SPRING 2016

An introduction to Geometric Measure Theory Part 2: Hausdorff measure

µ (X) := inf l(i k ) where X k=1 I k, I k an open interval Notice that is a map from subsets of R to non-negative number together with infinity

Measure Theory on Topological Spaces. Course: Prof. Tony Dorlas 2010 Typset: Cathal Ormond

2 Construction & Extension of Measures

ABSTRACT INTEGRATION CHAPTER ONE

Real Analysis II, Winter 2018

Analysis Comprehensive Exam Questions Fall 2008

MA359 Measure Theory

5 Set Operations, Functions, and Counting

Introduction to Ergodic Theory

x 0 + f(x), exist as extended real numbers. Show that f is upper semicontinuous This shows ( ɛ, ɛ) B α. Thus

SOME PROBLEMS IN REAL ANALYSIS.

Coin tossing space. 0,1 consisting of all sequences (t n ) n N, represents the set of possible outcomes of tossing a coin infinitely many times.

Probability and Measure. November 27, 2017

Three hours THE UNIVERSITY OF MANCHESTER. 24th January

MAT 571 REAL ANALYSIS II LECTURE NOTES. Contents. 2. Product measures Iterated integrals Complete products Differentiation 17

The Borel-Cantelli Group

Measure Theoretic Probability. P.J.C. Spreij

Section 2: Classes of Sets

Thus, X is connected by Problem 4. Case 3: X = (a, b]. This case is analogous to Case 2. Case 4: X = (a, b). Choose ε < b a

Final. due May 8, 2012

CHAPTER I THE RIESZ REPRESENTATION THEOREM

2 (Bonus). Let A X consist of points (x, y) such that either x or y is a rational number. Is A measurable? What is its Lebesgue measure?

Class Notes for Math 921/922: Real Analysis, Instructor Mikil Foss

Part V. 17 Introduction: What are measures and why measurable sets. Lebesgue Integration Theory

Measure Theoretic Probability. P.J.C. Spreij. (minor revisions by S.G. Cox)

REAL ANALYSIS I Spring 2016 Product Measures

Lebesgue Measure. Chapter Lebesgue Outer Measure

MAT 570 REAL ANALYSIS LECTURE NOTES. Contents. 1. Sets Functions Countability Axiom of choice Equivalence relations 9

Dynamical Systems 2, MA 761

Compendium and Solutions to exercises TMA4225 Foundation of analysis

RS Chapter 1 Random Variables 6/5/2017. Chapter 1. Probability Theory: Introduction

consists of two disjoint copies of X n, each scaled down by 1,

REAL AND COMPLEX ANALYSIS

4. Product measure spaces and the Lebesgue integral in R n.

A List of Problems in Real Analysis

Reminder Notes for the Course on Measures on Topological Spaces

Measure Theory and Integration

(1) Consider the space S consisting of all continuous real-valued functions on the closed interval [0, 1]. For f, g S, define

JOININGS, FACTORS, AND BAIRE CATEGORY

Transcription:

3. (a) Let M be an infinite σ-algebra of subsets of some set X. There exists a countably infinite subcollection C M, and we may choose C to be closed under taking complements (adding in missing complements if necessary). For each x X, define D x := {C C x C}, so that D x M. Let x, y X and suppose y D x. Then y C for all C C with x C. Moreover, if y C for some C C, then y / C c C, so x / C c and hence x C. This implies that, if C C, then x C iff y C. In particular D x = D y. If x, y X and there exists z D x D y, then D x = D z = D y, so the collection D := {D x x X} is pairwise disjoint. If C C, then C = {D x x C}, since x D x C for all x C. Therefore, the image of the map : 2 D 2 X contains C, so there exists a surjection from some subset of 2 D onto C. If D were finite, then 2 D would be as well, which is a contradiction because C is infinite. Therefore D is an infinite, pairwise disjoint subcollection of M. (b) Let M be an infinite σ-algebra of subsets of some set X. By the previous exercise, there exists an infinite, pairwise disjoint subcollection D of M. Since Q is countable, there exists an injection q : Q D. Define r : 2 Q M by r(a) := a A q(a). Then r is well-defined because each A Q is countable, and injective because D is pairwise disjoint. There exists an injection from R 2 Q, for example the map x (, x] Q (which is injective by the least upper bound property of R). Composing these injections gives an injective map from R M, which shows that card(m) c. 4. Let A be an algebra which is closed under countable increasing unions. To show that A is a σ-algebra, it suffices to show that it is closed under arbitrary countable unions. To this end, let {E n } be a countable collection of members of A. For each n N define F n := n E k. Since A is an algebra it is clear that (F n ) is an increasing sequence of members of A, so E n = F n A as required. Conversely, it is plain that every σ-algebra is closed under countable increasing unions. 5. Let E be a collection of subsets of some set X, and let M be the σ-algebra generated by E. Define N := {A A is the σ-algebra generated by some countable subcollection of E}. It is clear that, X N, E N and N is closed under taking complements. Let {E n } be a countable collection of members of N. For each n N there exists a countable subcollection E n of E such that E n is in the σ-algebra generated by E n. Since union of countably many countable sets is countable, F := E n is a countable subcollection of E. Let A be the σ-algebra generated by F, so that A N. For each n N the σ-algebra generated by E n is a subset of A, because A is a σ-algebra containing E n. This implies that E n A for all n N, and hence E n A N. Therefore N is closed under countable unions, so it is a σ-algebra containing E. This implies that M N. Conversely, let E N. Then E belongs to the σ-algebra A generated by some countable subcollection of E. Since M is a σ-algebra containing this subcollection, A M and hence E M. This shows that N M and hence N = M. 6. Note that µ( ) = µ( ) = µ( ) = 0. Given a sequence (A n ) of disjoint sets in M, there exists a sequence (E n ) of sets in M and a sequence (F n ) of subsets of measure zero sets from M such that A n = E n F n for all n N. Note that (E n ) is pairwise disjoint, and F n is a subset of a measure zero set. Therefore µ( A n ) = µ(( E n ) ( F n )) = µ( E n ) = µ(e n ) = µ(a n ). This shows that µ is a measure. Let A X, and suppose there exists B M such that A B and µ(b) = 0. Then B = E F for some E M and F a subset of a measure zero set N M. It follows that A E N, where E N M and µ(e N) µ(e) + µ(n) = µ(e) + 0 µ(b) = 0. Therefore A = A M, which shows that µ is complete. 1

Let λ : M [0, ] be another measure which extends µ, and let A M. Then A = E F for some E M and F a subset of a measure zero set N M. It follows that µ(e) = λ(e) λ(a) λ(e) + λ(f ) λ(e) + λ(n) = µ(e) + µ(n) = µ(e). Therefore λ(a) = µ(e) = µ(a), so λ = µ. This shows that µ is the unique measure on M which extends µ. 7. Set µ := n j=1 a jµ j, and note that µ( ) = 0. If {E i } i N is a pairwise disjoint collection of members of M, then µ( i N E i ) = a j µ j ( i N E i ) = j=1 a j j=1 µ j (E i ) = a j µ j (E i ) = i N i N j=1 i N (note that we are allowed to change the order of summation because all the terms are non-negative; alternatively you µ(e i ) can consider the convergent/divergent cases separately). This shows that µ is a measure on (X, M). 8. Let (X, M, µ) be a measure space and {E n } a countable collection of measurable sets. Then ( k=n E k) is an increasing sequence of measurable sets with µ( k=n E k) µ(e n ) for all n N, so µ(lim inf E n) = µ( ( k=n E k)) = lim n µ( k=n E k) = lim inf n µ( k=n E k) lim inf n µ(e n). Moreover ( k=n E k) is a decreasing sequence of measurable sets with µ( k=n E k) µ(e n ), so µ(lim sup E n ) = µ( ( k=n E k)) = lim n µ( k=n E k) = lim sup n provided that the first term of the sequence has finite measure, i.e. µ( E k) <. µ( k=n E k) lim sup µ(e n ) n 9. Let (X, M, µ) be a measure space and E, F M. Then E = (E F ) (E \ F ) and (E \ F ) F = E F, so µ(e) + µ(f ) = µ(e F ) + µ(e \ F ) + µ(f ) = µ(e F ) + µ(e F ). 10. Clearly µ E ( ) = µ( E) = µ( ) = 0. If {E n } is a pairwise disjoint collection of members of M, then µ E ( E n ) = µ(( E n ) E) = µ( (E n E)) = µ(e n E) = µ E (E n ). Therefore µ E is a measure. 11. Suppose that µ is continuous from below. Let {E n } be a pairwise disjoint collection of measurable sets, and for each n N define F n := n i=1 E n. Since µ is continuous from below and finitely additive, µ( i N E i ) = µ( F n ) = lim n µ(f n) = lim n µ(e i ) = i=1 µ(e i ). i=1 This shows that µ is a measure. Conversely, if µ is a measure it is continuous from below by Theorem 1.8. Now suppose that µ(x) < and µ is continuous from above. If (E n ) is an increasing sequence of measurable sets, then (E c n) is a decreasing sequence of measurable sets, which implies that µ( E n ) = µ(x) µ(( E n ) c ) = µ(x) µ( E c n) = µ(x) lim n µ(ec n) = lim n µ(e n). This shows that µ is continuous from below, so it is a measure by the previous paragraph. Conversely, if µ is a (finite) measure it is continuous from above by Theorem 1.8. 2

14. Suppose for a contradiction that there exists C (0, ) such that every measurable subset F E satisfies µ(f ) C or µ(f ) =. Set M := sup{µ(f ) F E is measurable and µ(f ) < }, and note that 0 M C. For each n N there exists a measurable subset E n E such that M n 1 µ(e n ) <. Set F n := n i=1 E n for each n N and define F := F n. Note that M n 1 µ(e n ) µ(f ) and also µ(f n ) n i=1 µ(e n) < for all n N, so M µ(f ) = lim n µ(f n ) M. This shows that µ(f ) = M, so µ(e \ F ) =. Since µ is semifinite, there exists a measurable subset A E \ F such that 0 < µ(a) <. This contradicts the definition of M, because A F E but µ(f ) < µ(a) + µ(f ) = µ(a F ) <. Therefore, for any C (0, ) there exists a measurable subset F E such that C < µ(f ) <. 17. Let A, B X be disjoint µ -measurable sets, and let E X. Then (A B) A c = B and hence µ (E (A B)) = µ (E (A B) A) + µ (E (A B) A c ) = µ (E A) + µ (E B). It follows by induction that n µ (E A k ) = µ (E ( n A k)) µ (E ( A k)) for all n N. Therefore µ (E A k ) µ (E ( A k)), which implies that µ (E ( A k)) = µ (E A k ) because µ is subadditive. 18. (a) Let E X and ε (0, ). If µ (E) = then X A A σ, E X and µ (X) µ (E) + ε. Otherwise { } µ (E) = inf µ 0 (A n ) A n A for all n N and E A n, so there exists a sequence (A n ) in A such that E A n and µ 0(A n ) µ (E) + ε. If A := A n, then A A σ, E A and µ (A) µ 0(A n ) µ (E) + ε. (b) Let E X such that µ (E) <. Suppose that E is µ -measurable. For each n N there exists B n A σ such that E B n and µ (B n ) µ (E) + n 1. Define B := B n, so that B A σδ and E B. Since µ (E) <, it follows that µ (B \ E) µ (B n E c ) = µ (B n ) µ (B n E) = µ (B n ) µ (E) n 1 for all n N. This implies that µ (B \ E) = 0. Conversely, suppose there exists B A σδ such that E B and µ (B \ E) = 0. If F X, then µ (F E) + µ (F E c ) µ (F B) + µ (F B c ) + µ (F (B \ E)) µ (F B) + µ (F B c ) = µ (F ) because B A σδ is µ -measurable. Clearly µ (F ) µ (F E) + µ (F E c ), so E is µ -measurable. 19. If E X is µ -measurable, then µ (X) = µ (X E)+µ (X E c ) = µ (E)+µ (E c ) by definition, so µ (E) = µ (E). Conversely, let E X and suppose that µ (E) = µ (E). By the previous exercise, for each n N there exist A n, B n A σ such that E A n, E c B n, µ (A n ) µ (E) + n 1 and µ (B n ) µ (E c ) + n 1. If A := A n, then µ (A \ E) µ (A n B n ) = µ (A n ) µ (A n \ B n ) = µ (A n ) µ (B c n) = µ (A n ) (µ (X) µ (B n )) µ (E) + n 1 µ (X) + µ (E c ) + n 1 3

= µ (E) µ (E) + 2n 1 = 2n 1 for all n N, and hence µ (A\E) = 0. Moreover E A and A A σδ, so by the previous exercise E is µ -measurable. 20. (a) If (A n ) is a sequence in M such that E A n, then µ (E) µ ( A n ) µ (A n ) = µ(a n ). Therefore µ (E) µ + (E), by definition. If there exists A M such that E A and µ (A) = µ (E), then µ + (E) µ(a) + µ( ) = µ (A) = µ (E), n=2 so µ (E) = µ + (E). Conversely, suppose that µ (E) = µ + (E). By exercise 18 part (a), for each n N there exists A n M σ = M such that E A n and µ + (A n ) µ + (E) + n 1. Define A := A n, so that A M and E A. Moreover µ + (A) µ + (A n ) µ + (E) + n 1 for all n N, so µ + (A) µ + (E). It follows that µ (A) = µ + (A) = µ + (E) = µ (E), because A M and E A. (b) Let µ 0 be a premeasure on an algebra A M such that µ is induced by µ 0, and let E X. By exercise 18 part (a), for each n N there exists A n A σ M such that E A n and µ (A n ) µ (E) + n 1. Define A := A n, so that A M and E A. Moreover µ (A) µ (A n ) µ (E) + n 1 for all n N, so µ (A) µ (E). It follows that µ (A) = µ (E), because E A. By the previous exercise, this implies that µ (E) = µ + (E). Therefore µ = µ +. (c) Define µ : 2 X [0, ] by µ ( ) = 0, µ ({0}) = 2, µ ({1}) = 2 and µ (X) = 3. Clearly µ (A) µ (B) for all A B X. Moreover µ is subadditive, because µ (X) < µ ({0}) + µ ({1}). Therefore µ is an outer measure. Note that {0} is not µ -measurable, because µ (X) = 3 < 2 + 2 = µ (X {0}) + µ (X {0} c ). This implies that µ + ({0}) = inf{ µ (A n ) A n X for all n N and A n = X for some n N} = µ (X) = 3 2 = µ ({0}). 21. Let E X be locally µ -measurable, and let A X. If µ (A) =, then clearly µ (A E) + µ (A E c ) µ (A). Otherwise, by exercise 18 part (a), for each n N there exists a µ -measurable set A n X such that A A n and µ (A n ) µ (A) + n 1. In particular, if n N then µ (A n ) <, and hence A n E and A n E c = A n (A n E) c are µ -measurable (because E is locally µ -measurable). It follows that µ (A E) + µ (A E c ) µ (A n E) + µ (A n E c ) = µ(a n E) + µ(a n E c ) = µ(a n ) = µ (A n ) µ (A) + n 1 for all n N, so µ (A E) + µ (A E c ) µ (A). Clearly µ (A) µ (A E) + µ (A E c ) in either case, so E is µ -measurable. This shows that µ is saturated. 22. (a) Clearly µ M = µ, so by exercise 6 from section 1.3 it suffices to show that M = M. To this end, let A M. Then A = E F for some E M and F X such that F B for some B M with µ(b) = 0. Clearly A E B M = M σδ and µ ((E B) \ A) µ (B) = 0. By exercise 18 part (c), it follows that A M. Conversely, let A M. By exercise 18 part (c) there exists B M σδ = M such that A B and µ (B \ A) = 0. Since B \ A M, exercise 18 part (b) implies that B \ A E and µ (E \ (B \ A)) = 0 for some E M. Note that B \ E M and A E M. Moreover µ (A E) µ (E \ (B \ A)) = 0, so there exists F M such that A E F and µ (F \ (A E)) = 0, by exercise 18 part (b). It follows that µ(f ) = µ (F ) µ (F \ (A E)) + µ (A E) = 0. 4

Since A = (B \ E) (A E), it follows that A M. Therefore M = M. (b) Let Ẽ M, and µ be the completion of µ. Given A M with µ(a) <, the converse of the previous exercise implies that A M (using exercise 18 part (b) instead of part (c)). Hence A = E F for some E M and F X such that F B for some B M with µ(b) = 0. In particular µ(a) = µ(e) = µ (E) µ (A) <. Therefore Ẽ A M, as Ẽ is locally µ-measurable. Since µ (Ẽ A) < the previous exercise implies that Ẽ A M (again using exercise 18 part (b) instead of part (c)). This shows that Ẽ is locally µ -measurable, so Ẽ M by exercise 21. Conversely, let Ẽ M and A M be such that µ(a) <. Then A = E F for some E M and F X such that F B for some B M with µ(b) = 0. It follows that µ (Ẽ A) µ (A) µ (E) + µ (F ) = µ(e) + 0 = µ(a) <. This implies that A M (by the previous exercise using part (b) instead of part (c)), so Ẽ A M and hence Ẽ A M (again by the previous exercise). This shows that Ẽ is locally µ-measurable, so Ẽ M. Therefore M = M. By exercise 6 from section 1.3, µ and µ agree on M. If E M \ M, then µ(e) = by definition. Moreover, if E M = M and µ(e) <, then E M by the previous exercise (using part (b) instead of part (c)). This implies that µ and µ also agree on M \ M. 23. (a) Let E := {(a, b] Q a, b R}. Clearly = (0, 0] Q E. If (a 1, b 1 ] Q E and (a 2, b 2 ] Q E then their intersection is (max{a 1, a 2 }, min{b 1, b 2 }] Q E. Moreover, the complement of (a, b] Q E is ((, a] Q) ((b, ] Q), which is a disjoint union of elements of E provided that a b. If a > b then the complement of (a, b] Q is just (, ] Q E. This shows that E is an elementary family of subsets of Q, so the collection of finite disjoint unions of members of E is an algebra. If (a 1, b 1 ] Q E and (a 2, b 2 ] Q E are not disjoint, then their union is (min{a 1, a 2 }, max{b 1, b 2 }] Q E. Therefore A is the collection of finite disjoint unions of members of E, so A is an algebra. (b) Let M be the σ-algebra generated by A. Since Q is countable and M is closed under countable unions, it suffices to show that {x} M for all x Q. Given x Q and n N, it is clear that (x 1 n, x] Q M. Therefore {x} = ((x 1 n, x] Q) M, as required. (c) By definition µ 0 ( ) = 0. Let (E n ) be a sequence of disjoint members of A whose union lies in A. If E n = for all n N, then E n = and hence µ 0 ( E n ) = 0 = µ 0(E n ). Otherwise E n, and E m for some m N, so µ 0 ( ) = and µ 0(E n ) µ 0 (E m ) =. Therefore µ 0 is a premeasure on A. Define µ 1, µ 2 : 2 Q [0, ] by, E µ 1 (E) = 0, E =, E contains 2 n m for some m Z and n N and µ 1 (E) = 0, otherwise. Clearly µ 1 A = µ 0 = µ 2 A, because every non-empty interval contains a rational of the form 2 n m for some m Z and n N. For the same reason that µ 0 is a premeasure, µ 1 is a measure. A very similar argument implies that µ 2 is a measure. But µ 1 µ 2 because µ 1 ({3 1 }) = whereas µ 2 ({3 1 }) = 0. 24. (a) Since µ(a) + µ(a c B) = µ(a B) = µ(b) + µ(b c A), by symmetry it suffices to show that µ(a c B) = 0. To this end, note that E A B c = (A c B) c (if a member of E is not in B c, it is in B E = A E A). So µ(x) = µ (X) = µ (E) µ ((A c B) c ) = µ((a c B) c ) = µ(x) µ(a c B), and hence µ(a c B) = 0 as required. 5

(b) It is clear that M E is a σ-algebra on E and that ν( ) = 0. Let {E n } be a pairwise disjoint subset of M E. For each n N there exists A n M such that E n = A n E. Set A := i N j=i+1 (A i A j ) and define B n := A n \ A for each n N. It is easily checked that {B n } is a pairwise disjoint subset of M and that E n = B n E for all n N. Therefore ν( E n ) = ν( (B n E)) = ν(( B n ) E) = µ( B n ) = µ(b n ) = ν(e n ), which shows that ν is a measure on M E. 25. Let (C n ) be a sequence of compact intervals covering R, and fix n N. There exists a G δ set V n M µ and a null set N n M µ such that E C n = V n \ N n. Let (V nk ) k N be a sequence of open sets such that V n = k N V nk. For each k N define an open set U nk := V nk C c n, and set U := n,k N U nk. Then U is a G δ set and U \ E N n. Indeed, if x U \ E there exists n N such that x C n, which implies that x V nk for all k N and hence x V n but x / E C n = V n \ N n. Moreover E U, because E U nk for all n, k N. It follows that E = U \ (U \ E), where U \ E is a null set. If n N, then E C n = H n N n for some F σ set H n M µ and some null set N n M µ. Clearly H n and N n are respectively F σ and null sets. Moreover E = (E C n ) = ( H n ) ( N n ). 26. Let E M µ and suppose that µ(e) <. Given ε (0, ), there exists an open set U M µ such that E U and µ(u) < µ(e) + ε 2. Let (U n) be a sequence of disjoint open intervals such that U n = U. Then µ(u n ) = µ(u) <, so there exists N N such that n=n+1 µ(u n) < ε 2. Define A := N n=1 U n. It follows that µ(e A) µ(e \ A) + µ(a \ E) µ(e \ U) + µ(u \ A) + µ(u \ E) = 0 + 28. Let a, b R. Since µ F is continuous from above, n=n+1 µ(u n ) + µ(u) µ(e) < ε. µ F ([a, b]) = µ F ( (a n 1, b]) = lim n µ F ((a n 1, b]) = lim n (F (b) F (a n 1 )) = F (b) F (a ). It follows that µ F ({a}) = µ F ([a, a]) = F (a) F (a ), in which case µ F ([a, b)) = µ F ([a, b]) µ F ({b}) = F (b ) F (a ) and µ F ((a, b)) = µ F ([a, b)) µ F ({a}) = F (b ) F (a). 29. (a) Suppose that E N but m(e) > 0. Define R := Q [0, 1), and for each r R set E r := E + r. Clearly each E r is measurable with m(e r ) = m(e), and r R E r [0, 2). Let r, s R and suppose that E r intersects E s. Then there exists t E r E s, so that t r, t s E N. Since t r = (t s) + (s r) and s r Q, the definition of N implies that t s = t r. Therefore r = s, which shows that {E r } r R is pairwise disjoint. Hence = r R m(e) = r R m(e r ) = m( r R E r ) m([0, 2)) = 2, which is a contradiction. Therefore m(e) = 0. 6

(b) Suppose that m(e) > 0, but every subset of E is measurable. Since E = n Z (E [n, n + 1)), there exists n Z such that m(e [n, n + 1)) > 0. Define F := (E [n, n + 1)) n, so that F [0, 1), m(f ) > 0 and every subset of F is measurable. Also define R := Q [ 1, 1], and for each r R set N r := N + r. It is clear that [0, 1) r R N r, and hence F = r R (F N r ). If r R then F N r F and (F N r ) r N, which implies that both subsets are measurable (by containment in F and translational invariance) and have measure zero (by the previous exercise and translational invariance). Therefore m(f ) r R m(f N r) = r R 0 = 0, which is a contradiction so not every subset of E is measurable. 30. Let E L with m(e) > 0, and suppose there exists α (0, 1) such that m(e I) αm(i) for all open intervals I. Without loss of generality m(e) < (since m is semifinite, we may replace E by a subset of finite positive measure). Define ε := m(e)(1 α), so that ε > 0. Since E L and m is outer regular, there exists an open set U R such that E U and m(u) < m(e) + ε. As U is open, there exists a pairwise disjoint collection {I i } i N of open intervals such that U = i N I i, and these intervals are bounded because m(u) <. If if i N then m(i i ) = m(i i \ E) + m(e I i ) m(i i \ E) + αm(i i ) and hence (1 α)m(i i ) m(i i \ E). Since i N (I i \ E) = U \ E has measure m(u) m(e), it follows that (1 α)m(u) = (1 α) i N m(i i ) = i N (1 α)m(i i ) i N m(i i \ E) = m( i N (I i \ E)) < ε = (1 α)m(e) and hence m(u) < m(e) m(u), which is impossible. Thus, for each α (0, 1) there exists an open interval I such that m(e I) > αm(i). The same clearly holds for α (, 0]. 31. Let E L with m(e) > 0, and set α := 3 4. By the previous exercise there exists a open interval I R with endpoints a, b R such that m(e I) > αm(i). Suppose there exists x ( 1 2 m(i), 1 2m(I)) such that x / E E. Then x / E E, and clearly 0 E E, so we may assume x > 0. Moreover E (E c + x) (E c x). Note that (a, a + 2x] I, because 2x < m(i) = b a. Define n := max{k N a + 2kx < b}, so that m(e (a, a + 2nx]) = (m(e (a + 2(k 1)x, a + (2k 1)x]) + m(e (a + (2k 1)x, a + 2kx])) (m((e c x) (a + 2(k 1)x, a + (2k 1)x]) + m((e c + x) (a + (2k 1)x, a + 2kx])) (m(e c (a + (2k 1)x, a + 2kx] x) + m(e c (a + 2(k 1)x, a + (2k 1)x] + x)) (m(e c (a + (2k 1)x, a + 2kx]) + m(e c (a + 2(k 1)x, a + (2k 1)x])) m(e c (a, a + 2nx]). This implies that m(e (a, a + 2nx]) 1 2 (m(e (a, a + 2nx]) + 1 2 m(ec (a, a + 2nx])) = 1 2m((a, a + 2nx]) = nx. Note that 4nx m(i), since otherwise k := 2n satisfies a + 2kx < b (but k > n). It follows that m(e I) m(e (a, a + 2nx]) + m((a + 2nx, b)) m(i) nx m(i) m(i) 4 = 3m(I) 4 = αm(i). This is a contradiction, so there does not exist x ( 1 2 m(i), 1 2m(I)) such that x / E E. 7

33. Choose a surjection q : N Q [0, 1], and for each n N define I n := (q(n) 3 n, q(n) + 3 n ). For each n N, define D n = I n \ ( k=n+1 I k). If m, n N and m < n, then D m D n = because D n I n k=m+1 I k. Moreover 2 3 n = m(i n ) m(d n ) + m( k=n+1 I k) m(d n ) + m(i k ) = m(d n ) + 2 3 k = m(d n ) + 3 n, k=n+1 k=n+1 and hence m(d n ) 3 n, for all n N. For each n N there exists a Borel set A n D n such that 0 < m(a n ) < 3 n, which can be found by intersecting D n with an interval of the form [3 n 1 k, 3 n 1 (k + 1)] for some k Z (not all of the intersections can have zero measure). Define A := [0, 1] ( A n ), and let I be a subinterval of [0, 1] with midpoint c. There exists n N such that 4 3 n < m(i), and there are infinitely many rationals in (c 3 n, c + 3 n ), so there exists k N with k n and q(k) (c 3 n, c + 3 n ). It follows that I k (c 2 3 n, c + 2 3 n ) I. Therefore A k A I (since A k I k [0, 1]), so m(a I) m(a k ) > 0. Moreover m(a I) = m(( A n ) I) = m(a k ) + m(( \{k} A n ) I) < m(d k ) + m(i \ D k ) = m(i), because m(a k ) < m(d k ) and \{k} A n \{k} D n Dk c. 8