앤더슨의 경영통계학 또는 오늘밤은 잠들 수 없어 > NEW도서

앤더슨의 경영통계학



도서명 : 앤더슨의 경영통계학
저자/출판사 : Anderson,Sweeney,Williams, 한올출판사
쪽수 : 708쪽
출판일 : 2022-03-05
ISBN : 9791166471933
정가 : 39000

Chapter 1 자료와 통계학
블룸버그 비즈니스위크 - NEW YORK, NEW YORK················4
1 경영 및 경제 분야에서의 활용············································5
?1. 회계············································································5
?2. 재무············································································6
?3. 마케팅 ········································································6
?4. 생산운영관리·································································6
?5. 경제············································································6
?6. 정보시스템···································································7
2 자료·················································································7
?1. 원소, 변수, 관측값 ·························································7
?2. 측정을 위한 척도····························································9
?3. 범주형 자료와 양적 자료················································ 10
?4. 횡단면 자료와 시계열 자료·············································· 10
3 자료의 출처···································································· 13
?1. 현존하는 자료······························································ 13
?2. 관측연구···································································· 15
?3. 실험·········································································· 15
?4. 시간과 비용 이슈·························································· 16
?5. 자료 수집 오류····························································· 16
4 기술통계········································································ 16
5 통계적 추론···································································· 18
6 엑셀을 활용한 통계분석···················································20
?1. 데이터 세트와 엑셀 워크시트··········································· 20
?2. 통계분석에서의 엑셀 활용··············································· 21
7 애널리틱스·····································································22
8 빅데이터와 데이터 마이닝················································23
9 통계분석을 위한 윤리적 지침···········································24
?요점정리··································································· 26
?보충문제··································································· 26
Chapter 2 기술통계: 표와 그래프를 이용한 표현
콜게이트-NEW YORK, NEW YORK·····································34
1 범주형 자료 요약·····························································35
?1. 도수분포표································································· 35
?2. 상대도수분포표와 백분율도수분포표································· 36
?3. 엑셀을 활용한 도수분포표, 상대도수분포표, 백분율도수분포표 작성 ········································································· 37
?4. 막대그래프와 원그래프·················································· 38
?5. 엑셀을 활용한 막대그래프 작성········································ 40
?연습문제··································································· 42
2 양적 자료 요약································································44
?1. 도수분포표································································· 44
?2. 상대도수분포표와 백분율도수분포표································· 46
?3. 엑셀을 활용한 도수분포표 작성········································ 46
?4. 점그래프···································································· 48
?5. 히스토그램································································· 49
?6. 엑셀을 활용한 히스토그램 작성········································ 50
?7. 누적도수분포······························································· 52
?8. 줄기-잎 그림······························································· 53
?연습문제··································································· 56
3 표를 이용한 두 변수 자료 요약 ········································· 59
?1. 교차표 ······································································ 59
?2. 엑셀 피봇 테이블을 활용한 교차표 작성······························ 61
?3. 심슨의 역설 ································································ 63
?연습문제··································································· 64
4 그래프를 이용한 두 변수 자료 요약···································66
?1. 산점도와 추세선··························································· 66
?2. 엑셀을 활용한 산점도와 추세선 작성································· 68
?3. 묶은 막대그래프와 누적 막대그래프 ································· 70
?4. 엑셀을 활용한 묶은 막대그래프와 누적 막대그래프 작성········· 72
?연습문제··································································· 73
5 자료 시각화: 효과적인 자료 시각화 방안 ·························· 75
?1. 효과적인 그래프 표현 방법·············································· 75
?2. 그래프 표현 형식 선택··················································· 76
?3. 데이터 대시보드··························································· 77
?4. 자료 시각화 사례: 신시내티 동물원과 식물원 ······················ 78
?요점정리··································································· 80
?보충문제··································································· 81
?사례연구 1. 펠리칸 스토어············································· 84
?사례연구 2. 영화 개봉··················································· 85
Chapter 3 기술통계: 수리적 측도를 이용한 표현
스몰 프라이 디자인-SANTA ANA, CALIFORNIA··················90
1 위치 측도······································································· 91
?1. 평균·········································································· 91
?2. 중앙값······································································· 93
?3. 최빈값······································································· 94
?4. 엑셀을 활용한 평균, 중앙값, 최빈값 계산···························· 94
?5. 가중평균···································································· 95
?6. 기하평균···································································· 96
?7. 엑셀을 활용한 기하평균 계산··········································· 98
?8. 백분위수···································································· 98
?9. 사분위수···································································· 99
?10. 엑셀을 활용한 백분위수, 사분위수 계산·····························100
?연습문제································································· 102
2 변동성 측도·································································· 106
?1. 범위·········································································107
?2. 사분위 범위································································107
?3. 분산·········································································107
?4. 표준편차···································································109
?5. 엑셀을 활용한 표본분산, 표본표준편차 계산·······················109
?6. 변동계수···································································110
?7. 엑셀의 기술통계 도구 활용·············································111?
?연습문제································································· 112
3 분포의 형태, 상대 위치, 이상값 검출 측도·························115
?1. 분포의 형태································································115
?2. z-점수······································································116
?3. 체비셰프의 정리··························································117
?4. 경험적 법칙································································118
?5. 이상값 탐지································································119?
?연습문제································································· 120
4 다섯 수치 요약과 상자그림············································· 123
?1. 다섯 수치 요약····························································123
?2. 상자그림···································································123
?3. 엑셀을 활용한 상자그림 작성··········································124
?4. 상자그림을 이용한 비교분석···········································125
?5. 엑셀을 활용한 상자그림 비교분석····································125?
?연습문제································································· 127
5 두 변수 간의 연관성 측도··············································· 130
?1. 공분산······································································130
?2. 공분산의 해석·····························································132
?3. 상관계수 ··································································134
?4. 상관계수의 해석··························································135
?5. 엑셀을 활용한 표본공분산, 표본상관계수 계산····················136
?연습문제································································· 137
6 데이터 대시보드···························································· 139
?요점정리································································· 142
?보충문제································································· 143
?사례연구 1. 펠리칸 스토어··········································· 147
?사례연구 2. 영화개봉················································· 148
?사례연구 3. 헤븐리 초콜릿 웹사이트 상거래······················ 149
?사례연구 4. 아프리카 코끼리 개체 수······························ 150
Chapter 4 확률 입문
미 항공우주국-WASHINGTON, DC··································· 154
1 확률실험, 계산규칙과 확률 부여하기······························ 155
?1. 계산규칙, 조합, 순열····················································156
?2. 확률 부여하기·····························································160
?3. 켄터키 전력회사 프로젝트의 확률····································162
?연습문제································································· 163
2 사건과 확률·································································· 165
?연습문제································································· 166
3 확률의 기본 법칙··························································· 168
?1. 여사건······································································168
?2. 확률의 덧셈법칙··························································169?
?연습문제································································· 172
4 조건부 확률···································································174
?1. 독립사건···································································177
?2. 확률의 곱셈법칙··························································178?
?연습문제································································· 179
5 베이즈 정리···································································181
?1. 표 접근법··································································185?
?연습문제································································· 186
?요점정리································································· 187
?보충문제································································· 187
?사례연구 1. 해밀턴 카운티의 판사들······························· 190
?사례연구 2. 랍스 마켓················································· 192
Chapter 5 이산확률분포
선거 유권자 대기시간····························································196
1 확률변수······································································ 197
?1. 이산확률변수······························································197
?2. 연속확률변수······························································198
?연습문제································································· 198
2 이산확률분포······························································· 199
?연습문제································································· 202
3 기댓값과 분산······························································· 204
?1. 기댓값······································································204
?2. 분산·········································································204
?3. 엑셀을 활용한 기댓값, 분산, 표준편차 계산························205?
?연습문제································································· 206
4 이변량 분포, 공분산, 재무 포트폴리오····························· 208
?1. 경험적 이변량 이산확률분포···········································209
?2. 재무분야 응용·····························································211?
?요점정리································································· 215?
?연습문제································································· 215
5 이항확률분포·································································217
?1. 이항실험···································································217
?2. 마틴 의류가게 문제······················································219
?3. 엑셀을 활용한 이항분포의 확률 계산································223
?4. 이항분포의 기댓값과 분산··············································225
?연습문제································································· 225
6 포아송 확률분포··························································· 227
?1. 시간의 구간을 포함하는 예제··········································228
?2. 길이 또는 거리를 포함하는 예제······································229
?3. 엑셀을 활용한 포아송 분포의 확률 계산·····························229
?연습문제································································· 232
?요점정리································································· 233
?보충문제································································· 234
?사례연구-맥닐의 자동차 판매점····································· 236
Chapter 6 연속확률분포
프록터 & 갬블 -CINCINNATI, OHIO ·································· 240
1 균일확률분포·································································241
?1. 확률척도로서의 면적····················································243
?연습문제································································· 244
2 정규확률분포······························································· 246
?1. 정규곡선···································································246
?2. 표준정규확률분포························································248
?3. 정규확률분포의 확률 계산··············································253
?4. 그리어 타이어 사례······················································254
?5. 엑셀을 활용한 정규분포의 확률 계산································256
?연습문제································································· 258
3 지수확률분포································································261
?1. 지수확률분포의 확률 계산··············································262
?2. 포아송 분포와 지수분포의 관계·······································263
?3. 엑셀을 활용한 지수분포의 확률 계산································264
?연습문제································································· 265
?요점정리································································· 266
?보충문제································································· 266
?사례연구 1. 스페셜티 토이즈········································ 269
?사례연구 2. 겝하르트 일렉트로닉스································ 270
Chapter 7 표본추출과 표본분포
식량농업기구-ROME, ITALY··············································· 274
1 전자공업협회의 표본추출 문제······································· 276
2 표본의 선택·································································· 276
?1. 유한 모집단에서의 표본추출···········································277
?2. 무한 모집단에서의 표본추출···········································281
?연습문제································································· 283
3 점추정········································································· 284
?1. 실질적 적용································································285
?연습문제································································· 286
4 표본분포의 개념··························································· 288
5 x의 표본분포······························································· 291
?1. x의 기댓값·······························································291
?2. x의 표준편차·····························································292
?3. x의 표본분포 형태······················································293
?4. EAI 예제에서 x의 표본분포··········································295
?5. x의 표본분포의 실질적 가치··········································295
?6. 표본크기와 의 표본분포 간의 관계································297
?연습문제································································· 299
6 p의 표본분포······························································ 301
?1. p의 기댓값································································302
?2. p의 표준편차·····························································302
?3. p의 표본분포 형태······················································303
?4. p의 표본분포의 실질적 가치··········································304
?연습문제································································· 305
7 기타 표본추출 방법······················································· 308
?1. 층화무작위추출···························································308
?2. 군집추출···································································309
?3. 계통추출···································································310
?4. 편의추출···································································310
?5. 판단추출···································································311
8 실질적 적용: 빅데이터와 표본추출의 오차························311
?1. 표본오차···································································311
?2. 비표본오차································································312
?3. 빅데이터···································································314
?4. 빅데이터에 대한 이해···················································315
?5. 빅데이터가 표본오차에 미치는 영향·································315?
?연습문제································································· 318
?요점정리································································· 321
?보충문제································································· 322
?사례연구-마리온 유업················································· 325
Chapter 8 구간추정
푸드라이온-SALISBURY, NORTH CAROLINA·················· 328
1 모집단 평균: σ를 아는 경우············································ 329
?1. 오차범위와 구간추정치·················································329
?2. 엑셀 활용하기·····························································333
?3. 실질적 조언································································335
?연습문제································································· 335
2 모집단 평균: σ 를 모르는 경우········································ 337
?1. 오차범위와 구간추정치·················································340
?2. 엑셀 활용하기·····························································341
?3. 실질적 조언································································342
?4. 소표본 사용하기··························································343
?5. 구간추정 절차 요약······················································344
?연습문제································································· 345
3 표본크기의 결정···························································· 347
?연습문제································································· 349
4 모집단 비율·································································· 351
?1. 엑셀 활용하기·····························································352
?2. 표본크기의 결정··························································354
?연습문제································································· 356
5 실질적 적용: 빅데이터와 구간추정·································· 359
?1. 빅데이터와 신뢰구간의 정밀도········································359
?2. 빅데이터가 신뢰구간에 미치는 영향·································361
?연습문제································································· 362
?요점정리································································· 363
?보충문제································································· 364
?사례연구 1. Young Professional 잡지··························· 368
?사례연구 2. 걸프 부동산·············································· 369
Chapter 9 가설검정
존 모렐 앤 컴퍼니-CINCINNATI, OHIO································374
1 귀무가설과 대립가설의 설정·········································· 375
?1. 연구가설 성격인 대립가설··············································375
?2. 이의제기 가정인 귀무가설··············································376
?3. 귀무가설과 대립가설 형식 요약·······································377
?연습문제································································· 378
2 제1종 오류와 제2종 오류··············································· 379
?연습문제································································· 381
3 모집단 평균: σ 를 알고 있는 경우···································· 382
?1. 단측검정···································································382
?2. 양측검정···································································388
?3. 엑셀을 활용한 분석······················································391
?4. 요약 및 실질적 적용을 위한 조언·····································392
?5. 가설검정과 구간추정과의 관계········································393
?연습문제································································· 395
4 모집단 평균: σ 를 모르는 경우········································ 398
?1. 단측검정···································································399
?2. 양측검정···································································400
?3. 엑셀을 활용한 분석······················································401
?4. 요약 및 실질적 적용·····················································403
?연습문제································································· 404
5 모비율·········································································· 407
?1. 엑셀을 활용한 분석······················································409
?2. 요약 및 실질적 적용·····················································410
?연습문제································································· 411
6 실질적 적용: 빅데이터와 가설검정···································414
?1. 빅데이터, 가설검정, p- 값·············································414
?2. 가설검정에서 빅데이터의 영향········································415
?연습문제································································· 416
?요점정리································································· 417
?보충문제································································· 418
?사례연구 1. 품질협회················································· 421
?사례연구 2. 베이뷰대학 경영대학 학생들의 윤리적 행동········ 422
Chapter 10 두 모집단 간 평균과 비율에 대한 추론
미국 식품의약청-WASHINGTON, D.C.······························· 426
1 두 모집단 평균 차이에 대한 추론: σ1?과 σ2?를 알고 있을 때·· 427
?1. μ1?? μ2?의 구간추정······················································427
?2. 엑셀을 활용한 신뢰구간 추정··········································429
?3. μ1?? μ2?에 대한 가설검정···············································431
?4. 엑셀을 활용한 가설검정················································433
?5. 실질적 적용을 위한 조언···············································435
?연습문제································································· 435
2 두 모집단 평균 차이에 대한 추론: σ1?과 σ2?를 모를 때······· 437
?1. μ1?? μ2?의 구간추정······················································438
?2. 엑셀을 활용한 신뢰구간 추정··········································439
?3. μ1?? μ2?에 대한 가설검정···············································441
?4. 엑셀을 활용한 가설검정················································443
?5. 실질적 적용을 위한 조언···············································445
?연습문제································································· 445
3 두 모집단 평균 차이에 대한 추론: 대응표본····················· 448
?1. 엑셀을 활용한 가설검정················································450
?연습문제································································· 452
4 두 모집단 비율 차이에 대한 추론···································· 455
?1. p1?? p2의 구간추정·······················································455
?2. 엑셀을 활용한 신뢰구간 추정··········································457
?3. p1?? p2에 대한 가설검정················································459
?4. 엑셀을 활용한 가설검정················································460
?연습문제································································· 462
?요점정리································································· 464
?보충문제································································· 464
?사례연구-PAR INC.·················································· 466
Chapter 11 모분산에 대한 추론
미국 정부 회계감사원-WASHINGTON, D.C.······················· 470
1 모분산에 대한 추론························································471
?1. 구간추정···································································472
?2. 엑셀을 활용한 신뢰구간 추정··········································474
?3. 가설검정···································································476
?4. 엑셀을 활용한 가설검정················································479
?연습문제································································· 480
2 두 모분산에 대한 추정··················································· 482
?1. 엑셀을 활용한 가설검정················································487
?연습문제································································· 488
?요점정리································································· 490
?보충문제································································· 490
?사례연구-공군 훈련 프로그램······································· 492
Chapter 12 적합도, 독립성 및 모비율의 동일성 검정
공동모금-ROCHESTER, NEW YORK·································496
1 적합도 검정·································································· 497
?1. 다항확률분포······························································497
?2. 엑셀을 활용한 적합도 검정·············································501
?연습문제································································· 502
2 독립성 검정·································································· 503
?1. 엑셀을 활용한 독립성 검정·············································508
?연습문제································································· 509
3 3개 이상의 모집단에서 비율의 동일성 검정······················512
?1. 다중비교 절차·····························································515
?2. 엑셀을 활용한 모비율의 동일성 검정································517
?연습문제································································· 519
?요점정리································································· 521
?보충문제································································· 521
?사례연구 1. 푸엔티스 솔티 스낵····································· 523
?사례연구 2. 프레즈노 보드게임······································ 525
Chapter 13 실험설계 및 분산분석
버크 사-CINCINNATI, OHIO·············································· 528
1 실험설계의 소개와 분산분석·········································· 530
?1. 자료 수집··································································531
?2. 분산분석을 위한 가정···················································532
?3. 분산분석: 기본 개념·····················································533
2 분산분석과 완전확률화설계··········································· 535
?1. 처리 간 분산 추정치·····················································537
?2. 처리 내 분산 추정치·····················································537
?3. 분산 추정치의 비교: F검정·············································538
?4. 분산분석표································································540
?5. 엑셀을 활용한 분석······················································541
?6. k 개 모집단 평균의 동일성 검정: 관측연구··························543
?연습문제································································· 545
3 다중비교 절차······························································· 547
?1. 피셔의 LSD·······························································548
?2. 제1종 오류율······························································550?
?연습문제································································· 551
?요점정리································································· 553
?보충문제································································· 554
?사례연구-영업 전문가 보상·········································· 556
Chapter 14 단순선형회귀분석
월마트-BENTONVILLE, ARKANSAS································ 560
1 단순선형회귀모형··························································561
?1. 회귀모형과 회귀식·······················································561
?2. 회귀식의 추정·····························································562
2 최소제곱법··································································· 564
?1. 엑셀을 활용한 산점도, 추정회귀선, 추정회귀식 작성·············568
?연습문제································································· 569
3 결정계수······································································ 573
?1. 엑셀을 활용한 결정계수 계산··········································577
?2. 상관계수···································································578
?연습문제································································· 579
4 모형의 가정·································································· 581
5 유의성 검정·································································· 583
?1. σ2?의 추정··································································583
?2. t 검정·······································································584
?3. β1의 신뢰구간····························································586
?4. F 검정······································································586
?5. 유의성 검정 결과 해석에 대한 주의사항·····························588
?연습문제································································· 590
6 추정회귀식을 이용한 추정과 예측··································· 591
?1. 구간추정···································································592
?2. y 평균값의 신뢰구간····················································592
?3. y 개별값의 신뢰구간····················································594
?연습문제································································· 597
7 엑셀의 회귀분석 도구···················································· 598
?1. 아르만즈 피자 팔러 문제에 엑셀 회귀분석 도구 적용············598
?2. 추정회귀식 결과값 해석················································600
?3. 분산분석 결과값 해석···················································601
?4. 회귀분석 통계량 결과값 해석··········································602
?연습문제································································· 602
8 실질적 적용: 단순선형회귀분석에서 빅데이터와 가설검정·603
?요점정리································································· 604
?보충문제································································· 605
?사례연구 1. 주식시장 위험 측정····································· 607
?사례연구 2. 미교통부················································· 608
?사례연구 3. 포인트 앤드 슛 디지털 카메라 고르기··············· 609
?Appendix 14.1 미적분을 이용한 최소제곱 공식의 유도······· 611
?Appendix 14.2 상관관계를 이용한 유의성 검정················ 613
Chapter 15 다중회귀분석
인터내셔널 페이퍼-PURCHASE, NEW YORK······················618
1 다중회귀모형·································································619
?1. 회귀모형과 회귀식·······················································619
?2. 다중회귀식의 추정·······················································620
2 최소제곱법··································································· 621
?1. 예제: 버틀러 화물운송 회사············································621
?2. 엑셀의 회귀분석 도구를 이용하여 다중회귀식 추정하기·········624
?3. 계수 해석에 대한 주의사항·············································626
?연습문제································································· 626
3 다중결정계수································································ 630
?연습문제································································· 631
4 모형의 가정·································································· 633
5 유의성 검정·································································· 634
?1. F 검정·······································································635
?2. t 검정········································································637
?3. 다중공선성································································638
?연습문제································································· 640
6 추정과 예측을 위한 추정회귀방정식 활용························ 642
?연습문제································································· 643
7 범주형 독립변수···························································· 644
?1. 예제: 존슨 정수기회사··················································644
?2. 모수의 해석································································646
?3. 복잡한 범주형 변수······················································648
?연습문제································································· 649
?요점정리································································· 652
?보충문제································································· 652
?사례연구 1. 컨슈머 리서치사········································ 656
?사례연구 2. 최고의 자동차 찾기····································· 657
Appendixes
1 참고 문헌····································································· 660
2 부록 A········································································· 660
3 부록 B-분포표····························································· 662
4 부록 C-합을 표현하는 기호··········································· 673
5 부록 D-통계분석을 위한 엑셀 활용·································676




오늘밤은 잠들 수 없어



도서명 : 오늘밤은 잠들 수 없어
저자/출판사 : 미야베,미유키, 문학동네
쪽수 : 264쪽
출판일 : 2022-01-20
ISBN : 9788954684651
정가 : 15000

킥오프 9
전반전 13
하프타임 96
후반전 104
승부차기 206