앤더슨의경영통계학(8판)

[도서소개]

이 책은 Essentials of Modern Business Statistics with MicrosoftⓇ ExcelⓇ의 8판이다. 

이번 판에서는 두 명의 저명한 학자인 Cincinnati 대학의 Michael J. Fry와 Iowa 대학의 Jeffrey W. Ohlmann이 저자로 참여하였다. 

두 분 모두 통계 및 비즈니스 분석 분야에서 뛰어난 교수이자, 연구원, 실무자이다. 그들의 업적을 저자소개 부분에 자세히 기술하였다. 

Mike와 Jeff가 공동저자로 참여하면서 Essentials of Modern Business Statistics with Microsoft Excel의 효용성이 높아졌을 것으로 기대한다.

이 책은 경영학 및 경제학 분야의 학생들에게 통계에 대한 개념과 다양한 응용 사례를 소개하는 것이 목적이며, 수학적 지식이 부족한 독자들을 대상으로 서술되었다.

데이터 분석 및 통계 방법론은 이 책의 핵심적인 부분이다. 활용사례에서 각 방법에 대한 논의와 전개가 이루어지며 의사결정 및 문제 해결에 대한 통찰력을 제공하는 통계적 결과가 함께 제공된다.

이 책은 응용 중심으로 이루어져 있지만, 방법론에 대한 자세한 설명을 제공함과 동시에 각 주제에서 일반적으로 통용되는 표기법을 사용하려고 노력하였다. 

따라서 학생들에게는 이 책이 고급 통계학을 공부하기 위한 좋은 준비서가 될 것이다. 또한, 심도 있는 공부에 도움이 되는 참고문헌은 부록에 수록하였다.

[목차]

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

[역자소개]

대표역자

장영순(명지대학교)

역자

김도현(명지대학교) 

권영훈(경남대학교) 

김옹규(한밭대학교)

박진한(경남대학교) 

서종현(한국산업기술대학교) 

유태종(상명대학교)

이근철(건국대학교) 

허 정(한경대학교) 

황윤민(충북대학교)