- Page 1 and 2: � � � �1 2� � �3 1�
- Page 3 and 4: Preface In most mathematics program
- Page 5 and 6: dent projects for individuals or sm
- Page 7 and 8: Contents 1 Linear Systems 1 1.I Sol
- Page 9: 5.II.1 Definition and Examples ....
- Page 13 and 14: Section I. Solving Linear Systems 3
- Page 15 and 16: Section I. Solving Linear Systems 5
- Page 17 and 18: Section I. Solving Linear Systems 7
- Page 19 and 20: Section I. Solving Linear Systems 9
- Page 21 and 22: Section I. Solving Linear Systems 1
- Page 23 and 24: Section I. Solving Linear Systems 1
- Page 25 and 26: Section I. Solving Linear Systems 1
- Page 27 and 28: Section I. Solving Linear Systems 1
- Page 29 and 30: Section I. Solving Linear Systems 1
- Page 31 and 32: Section I. Solving Linear Systems 2
- Page 33 and 34: Section I. Solving Linear Systems 2
- Page 35 and 36: Section I. Solving Linear Systems 2
- Page 37 and 38: Section I. Solving Linear Systems 2
- Page 39 and 40: Section I. Solving Linear Systems 2
- Page 41 and 42: Section I. Solving Linear Systems 3
- Page 43 and 44: Section II. Linear Geometry of n-Sp
- Page 45 and 46: Section II. Linear Geometry of n-Sp
- Page 47 and 48: Section II. Linear Geometry of n-Sp
- Page 49 and 50: Section II. Linear Geometry of n-Sp
- Page 51 and 52: Section II. Linear Geometry of n-Sp
- Page 53 and 54: Section II. Linear Geometry of n-Sp
- Page 55 and 56: Section III. Reduced Echelon Form 4
- Page 57 and 58: Section III. Reduced Echelon Form 4
- Page 59 and 60: Section III. Reduced Echelon Form 4
- Page 61 and 62:
Section III. Reduced Echelon Form 5
- Page 63 and 64:
Section III. Reduced Echelon Form 5
- Page 65 and 66:
Section III. Reduced Echelon Form 5
- Page 67 and 68:
Section III. Reduced Echelon Form 5
- Page 69 and 70:
Section III. Reduced Echelon Form 5
- Page 71 and 72:
Topic: Computer Algebra Systems 61
- Page 73 and 74:
Topic: Input-Output Analysis 63 Top
- Page 75 and 76:
Topic: Input-Output Analysis 65 One
- Page 77 and 78:
Topic: Accuracy of Computations 67
- Page 79 and 80:
Topic: Accuracy of Computations 69
- Page 81 and 82:
Topic: Accuracy of Computations 71
- Page 83 and 84:
Topic: Analyzing Networks 73 of the
- Page 85 and 86:
Topic: Analyzing Networks 75 10 vol
- Page 87 and 88:
Topic: Analyzing Networks 77 We can
- Page 89 and 90:
Chapter 2 Vector Spaces The first c
- Page 91 and 92:
Section I. Definition of Vector Spa
- Page 93 and 94:
Section I. Definition of Vector Spa
- Page 95 and 96:
Section I. Definition of Vector Spa
- Page 97 and 98:
Section I. Definition of Vector Spa
- Page 99 and 100:
Section I. Definition of Vector Spa
- Page 101 and 102:
Section I. Definition of Vector Spa
- Page 103 and 104:
Section I. Definition of Vector Spa
- Page 105 and 106:
Section I. Definition of Vector Spa
- Page 107 and 108:
Section I. Definition of Vector Spa
- Page 109 and 110:
Section I. Definition of Vector Spa
- Page 111 and 112:
Section I. Definition of Vector Spa
- Page 113 and 114:
Section II. Linear Independence 103
- Page 115 and 116:
Section II. Linear Independence 105
- Page 117 and 118:
Section II. Linear Independence 107
- Page 119 and 120:
Section II. Linear Independence 109
- Page 121 and 122:
Section II. Linear Independence 111
- Page 123 and 124:
Section III. Basis and Dimension 11
- Page 125 and 126:
Section III. Basis and Dimension 11
- Page 127 and 128:
Section III. Basis and Dimension 11
- Page 129 and 130:
Section III. Basis and Dimension 11
- Page 131 and 132:
Section III. Basis and Dimension 12
- Page 133 and 134:
Section III. Basis and Dimension 12
- Page 135 and 136:
Section III. Basis and Dimension 12
- Page 137 and 138:
Section III. Basis and Dimension 12
- Page 139 and 140:
Section III. Basis and Dimension 12
- Page 141 and 142:
Section III. Basis and Dimension 13
- Page 143 and 144:
Section III. Basis and Dimension 13
- Page 145 and 146:
Section III. Basis and Dimension 13
- Page 147 and 148:
Section III. Basis and Dimension 13
- Page 149 and 150:
Section III. Basis and Dimension 13
- Page 151 and 152:
Topic: Fields 141 Topic: Fields Lin
- Page 153 and 154:
Topic: Crystals 143 Topic: Crystals
- Page 155 and 156:
Topic: Crystals 145 (To show the ad
- Page 157 and 158:
Topic: Voting Paradoxes 147 Topic:
- Page 159 and 160:
Topic: Voting Paradoxes 149 (Read t
- Page 161 and 162:
Topic: Voting Paradoxes 151 Voting
- Page 163 and 164:
Topic: Dimensional Analysis 153 arc
- Page 165 and 166:
Topic: Dimensional Analysis 155 whe
- Page 167 and 168:
Topic: Dimensional Analysis 157 the
- Page 169 and 170:
Chapter 3 Maps Between Spaces 3.I I
- Page 171 and 172:
Section I. Isomorphisms 161 1.3 Def
- Page 173 and 174:
Section I. Isomorphisms 163 The map
- Page 175 and 176:
Section I. Isomorphisms 165 relevan
- Page 177 and 178:
Section I. Isomorphisms 167 (d) f :
- Page 179 and 180:
Section I. Isomorphisms 169 (d) Sup
- Page 181 and 182:
Section I. Isomorphisms 171 2.4 Lem
- Page 183 and 184:
Section I. Isomorphisms 173 2.8 Exa
- Page 185 and 186:
Section I. Isomorphisms 175 (a) R 2
- Page 187 and 188:
Section II. Homomorphisms 177 (1) f
- Page 189 and 190:
Section II. Homomorphisms 179 1.9 T
- Page 191 and 192:
Section II. Homomorphisms 181 and a
- Page 193 and 194:
Section II. Homomorphisms 183 (b) S
- Page 195 and 196:
Section II. Homomorphisms 185 an im
- Page 197 and 198:
Section II. Homomorphisms 187 (u1,u
- Page 199 and 200:
Section II. Homomorphisms 189 To sh
- Page 201 and 202:
Section II. Homomorphisms 191 Next,
- Page 203 and 204:
Section II. Homomorphisms 193 2.38
- Page 205 and 206:
Section III. Computing Linear Maps
- Page 207 and 208:
Section III. Computing Linear Maps
- Page 209 and 210:
Section III. Computing Linear Maps
- Page 211 and 212:
Section III. Computing Linear Maps
- Page 213 and 214:
Section III. Computing Linear Maps
- Page 215 and 216:
Section III. Computing Linear Maps
- Page 217 and 218:
Section III. Computing Linear Maps
- Page 219 and 220:
Section III. Computing Linear Maps
- Page 221 and 222:
Section IV. Matrix Operations 211 3
- Page 223 and 224:
Section IV. Matrix Operations 213
- Page 225 and 226:
Section IV. Matrix Operations 215 w
- Page 227 and 228:
Section IV. Matrix Operations 217 I
- Page 229 and 230:
Section IV. Matrix Operations 219 W
- Page 231 and 232:
Section IV. Matrix Operations 221 t
- Page 233 and 234:
Section IV. Matrix Operations 223 3
- Page 235 and 236:
Section IV. Matrix Operations 225 I
- Page 237 and 238:
Section IV. Matrix Operations 227 3
- Page 239 and 240:
Section IV. Matrix Operations 229
- Page 241 and 242:
Section IV. Matrix Operations 231 t
- Page 243 and 244:
Section IV. Matrix Operations 233 4
- Page 245 and 246:
Section IV. Matrix Operations 235 T
- Page 247 and 248:
Section IV. Matrix Operations 237 W
- Page 249 and 250:
Section V. Change of Basis 239 1.2
- Page 251 and 252:
Section V. Change of Basis 241 Exer
- Page 253 and 254:
Section V. Change of Basis 243 (To
- Page 255 and 256:
Section V. Change of Basis 245 All
- Page 257 and 258:
Section V. Change of Basis 247 2.9
- Page 259 and 260:
Section V. Change of Basis 249 (c)
- Page 261 and 262:
Section VI. Projection 251 �v c
- Page 263 and 264:
Section VI. Projection 253 That is,
- Page 265 and 266:
Section VI. Projection 255 first on
- Page 267 and 268:
Section VI. Projection 257 We get
- Page 269 and 270:
Section VI. Projection 259 � �
- Page 271 and 272:
Section VI. Projection 261 This def
- Page 273 and 274:
Section VI. Projection 263 N M Noti
- Page 275 and 276:
Section VI. Projection 265 Exercise
- Page 277 and 278:
Section VI. Projection 267 (d) Find
- Page 279 and 280:
Topic: Line of Best Fit 269 Topic:
- Page 281 and 282:
Topic: Line of Best Fit 271 We clos
- Page 283 and 284:
Topic: Line of Best Fit 273 (b) Fin
- Page 285 and 286:
Topic: Geometry of Linear Maps 275
- Page 287 and 288:
Topic: Geometry of Linear Maps 277
- Page 289 and 290:
Topic: Geometry of Linear Maps 279
- Page 291 and 292:
Topic: Markov Chains 281 then goes
- Page 293 and 294:
Topic: Markov Chains 283 motivated
- Page 295 and 296:
Topic: Markov Chains 285 w = A * v;
- Page 297 and 298:
Topic: Orthonormal Matrices 287 Tha
- Page 299 and 300:
Topic: Orthonormal Matrices 289 �
- Page 301:
Topic: Orthonormal Matrices 291 4 I
- Page 304 and 305:
294 Chapter 4. Determinants 4.I Def
- Page 306 and 307:
296 Chapter 4. Determinants also do
- Page 308 and 309:
298 Chapter 4. Determinants 1.10 Sh
- Page 310 and 311:
300 Chapter 4. Determinants 2.3 Lem
- Page 312 and 313:
302 Chapter 4. Determinants � �
- Page 314 and 315:
304 Chapter 4. Determinants conflic
- Page 316 and 317:
306 Chapter 4. Determinants 3.4 Exa
- Page 318 and 319:
308 Chapter 4. Determinants To stat
- Page 320 and 321:
310 Chapter 4. Determinants We fini
- Page 322 and 323:
312 Chapter 4. Determinants 3.34 [A
- Page 324 and 325:
314 Chapter 4. Determinants then th
- Page 326 and 327:
316 Chapter 4. Determinants where t
- Page 328 and 329:
318 Chapter 4. Determinants 4.10 Gi
- Page 330 and 331:
320 Chapter 4. Determinants Compare
- Page 332 and 333:
322 Chapter 4. Determinants Proof.
- Page 334 and 335:
324 Chapter 4. Determinants � 1.1
- Page 336 and 337:
326 Chapter 4. Determinants 4.III O
- Page 338 and 339:
328 Chapter 4. Determinants by expa
- Page 340 and 341:
330 Chapter 4. Determinants (a) on
- Page 342 and 343:
332 Chapter 4. Determinants is, the
- Page 344 and 345:
334 Chapter 4. Determinants Topic:
- Page 346 and 347:
336 Chapter 4. Determinants (b) Tim
- Page 348 and 349:
338 Chapter 4. Determinants There a
- Page 350 and 351:
340 Chapter 4. Determinants Each of
- Page 352 and 353:
342 Chapter 4. Determinants That si
- Page 354 and 355:
344 Chapter 4. Determinants Because
- Page 356 and 357:
346 Chapter 4. Determinants [Ryan],
- Page 358 and 359:
348 Chapter 5. Similarity the examp
- Page 360 and 361:
350 Chapter 5. Similarity 1.10 Coro
- Page 362 and 363:
352 Chapter 5. Similarity Since mat
- Page 364 and 365:
354 Chapter 5. Similarity canonical
- Page 366 and 367:
356 Chapter 5. Similarity That is,
- Page 368 and 369:
358 Chapter 5. Similarity has an ei
- Page 370 and 371:
360 Chapter 5. Similarity The eigen
- Page 372 and 373:
362 Chapter 5. Similarity represent
- Page 374 and 375:
364 Chapter 5. Similarity � 3.32
- Page 376 and 377:
366 Chapter 5. Similarity has this
- Page 378 and 379:
368 Chapter 5. Similarity Exercises
- Page 380 and 381:
370 Chapter 5. Similarity 2.5 Examp
- Page 382 and 383:
372 Chapter 5. Similarity string in
- Page 384 and 385:
374 Chapter 5. Similarity (The �
- Page 386 and 387:
376 Chapter 5. Similarity That tabl
- Page 388 and 389:
378 Chapter 5. Similarity � 2.34
- Page 390 and 391:
380 Chapter 5. Similarity 1.3 Defin
- Page 392 and 393:
382 Chapter 5. Similarity 1.8 Theor
- Page 394 and 395:
384 Chapter 5. Similarity 1.12 Exam
- Page 396 and 397:
386 Chapter 5. Similarity (c) Decid
- Page 398 and 399:
388 Chapter 5. Similarity 2.4 Examp
- Page 400 and 401:
390 Chapter 5. Similarity ⌢ BR is
- Page 402 and 403:
392 Chapter 5. Similarity To prove
- Page 404 and 405:
394 Chapter 5. Similarity Taken tog
- Page 406 and 407:
396 Chapter 5. Similarity shows tha
- Page 408 and 409:
398 Chapter 5. Similarity (d) Show
- Page 410 and 411:
400 Chapter 5. Similarity Two imple
- Page 412 and 413:
402 Chapter 5. Similarity 39367 >v1
- Page 414 and 415:
404 Chapter 5. Similarity Knowing t
- Page 416 and 417:
406 Chapter 5. Similarity Introduci
- Page 418 and 419:
408 Chapter 5. Similarity Exercise
- Page 420 and 421:
410 Chapter 5. Similarity We recogn
- Page 422 and 423:
412 Chapter 5. Similarity 115292150
- Page 424 and 425:
A-2 And. Consider the statement for
- Page 426 and 427:
A-4 Venn diagrams aren’t very hel
- Page 428 and 429:
A-6 The other thing is that we some
- Page 430 and 431:
A-8 When two sets share no members
- Page 432 and 433:
A-10 the set {(a, b) � � a
- Page 434 and 435:
A-12 Usually when we pick represent
- Page 436 and 437:
[Anton] Howard Anton, Elementary Li
- Page 438 and 439:
[Kemeny & Snell] John G. Kemeny, J.
- Page 440 and 441:
Index accuracy of Gauss’ method,
- Page 442 and 443:
estriction, A-9 right inverse, 231
- Page 444 and 445:
matrix-vector, 197 mutual inclusion
- Page 446:
characteristic polynomial, 360 comp