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본서는 품질경영을 실천하기 위한 통계 방법을 소개하는 데 목표를 두고 있다.

통계적 품질관리란 품질관리의 한 유형으로서 통계학과 모든 통계 수단을 사용하여 품질특성값을 관리하는 것을 의미한다.

1930년대부터 본격적으로 대두된 통계적 품질관리는 종합적 품질관리(TQC)와 TQM이 소개된 후에도 통계적 품질관리 기법에서 더욱 다양하게 발전하였다.

Part 01 통계적 품질관리 기본과정

Chapter 01 품질관리와 통계적 방법 ············································· 4

1. 품질관리의 기초지식 ···························································· 4

1) 품질관리의 개념 4

2) 품질관리와 문제해결기법 10

2. 통계적 품질관리 ································································ 11

1) 품질관리의 기법 11

2) 통계적 방법 15

3. 통계량에 의한 데이터의 요약 ··········································· 20

1) 기본 통계량에 의한 요약 20

2) 기술 통계법에 의한 요약 27

3) 공정능력지수 31

Chapter 02 그래프에 의한 데이터의 시각화 ································· 36

1. 그래프의 기본사항 ······························································ 36

1) 그래프의 목적과 종류 36

2) Excel의 그래프 작성기능 40

2. 그래프의 실제 ·································································· 42

1) 단일회답의 그래프화 42

2) 복수회답의 그래프화 49

3) 크로스 집계결과의 그래프화 50

Chapter 03 파레토도 ········································································ 57

1. 파레토도의 기본사항 ·························································· 57

2. 파레토도의 실제 ································································ 60

1) 파레토도의 작성 60

2) 파레토도의 응용 66

Chapter 04 히스토그램 ····································································· 70

1. 히스토그램의 기본 ······························································ 70

2. 히스토그램의 작성방법 ······················································ 72

3. 히스토그램의 대용 그래프 ················································· 84

1) 도트 플롯 84

2) 함수 REPT에 의한 대용 그래프 89

Chapter 05 이산확률분포 ································································· 93

1. 이항분포 ············································································· 93

2. 포아송 분포 ····································································· 112

3. 초기하분포 ······································································· 126

Chapter 06 연속확률분포 ······························································· 133

1. 정규분포 ··········································································· 133

2. 표준 정규분포 ·································································· 144

3. 지수분포 ··········································································· 152

Chapter 07 데이터의 수집과 표본추출법 ····································· 159

1. 데이터의 종류와 수집방법 ··············································· 159

2. 표본추출의 기본개념 ······················································· 163

3. 무작위추출법 ···································································· 163

1) 단순무작위추출법(simple random sampling) 164

2) 계통추출법(systematic sampling) 164

3) 집락추출법(cluster sampling) 165

4) 층별추출법(stratified sampling) 165

5) 다단추출법(multi-stage sampling) 165

4. 유의선출법 ······································································· 166

5. 표본추출의 실제 ······························································ 167

Chapter 08 관리도 ·········································································· 175

1. 계량치 관리도 ·································································· 175

1) 관리도의 개요 175

2) ? -x?? - R 관리도의 작성방법 179

3)? ~x?? - R 관리도의 작성방법 186

4) x?? - R?s 관리도의 작성방법 190

2. 계수치 관리도 ·································································· 196

1) pn 관리도의 작성방법 196

2) p 관리도의 작성방법 200

3) c 관리도의 작성방법 204

4) u 관리도 206

5) 관리도의 해석방법 209

Chapter 09 샘플링검사 ··································································· 213

1. 샘플링검사의 계획 ··························································· 213

1) 샘플링검사의 기초 213

2) 샘플링검사의 이론 215

3) OC 곡선과 샘플링검사방식의 설계 223

4) OC 곡선의 성질 225

5) 샘플링검사방식과 이해관계자의 보호 233

6) 샘플링검사의 절차 236

2. 각종 샘플링검사 ······························································ 237

1) 계수 규준형 샘플링검사 237

2) 계수 선별형 샘플링검사 240

3) 계수 조정형 샘플링검사 242

4) 계수 연속생산형 샘플링검사 243

5) 계량 규준형 샘플링검사 244

Chapter 10 관능평가 ······································································ 246

1. 관능평가의 기본사항 ························································ 246

1) 관능평가의 개념 246

2) 감각의 성질 247

2. 관능평가의 의의 ······························································ 251

3. 관능평가의 의미 ······························································ 252

1) 관능이란 무엇인가 252

2) JIS에 의한 관능평가의 정의 253

4. 관능평가의 특징 ······························································ 255

1) 관능평가와 이화학적 검사의 비교 255

2) 관능평가의 특질 256

5. 관능평가에 있어서의 데이터의 성질 ······························· 258

1) 척도의 분류 258

2) 관능평가에 있어서의 데이터 259

3) ‘간주한다’고 하는 것 261

6. 관능평가의 실제 ······························································ 262

1) 관능평가 데이터의 표현방법 262

2) 관능평가를 위한 수법 263

7. 관능특성 데이터의 분석과 통계적 관능평가법 ····················· 267

1) 관능특성 데이터의 분석 267

2) 통계적 관능평가법의 개요 267

3) 통계적 관능평가의 실제 269

Part 02 통계적 품질관리 응용과정

Chapter 11 실험의 계획과 실시 ···················································· 274

1. 실험계획법 ········································································ 274

1) 실험의 추진방법 274

2) 실험계획법의 용어 277

3) 인자의 종류 279

2. 실험의 실시 ····································································· 281

1) 실험의 원칙 281

2) 실험의 형식 284

Chapter 12 일원배치 실험 ····························································· 291

1. 일원배치 실험의 계획과 해석 ·········································· 291

1) 실험순서의 랜덤화 291

2) 분산분석의 이론 294

2. 데이터 분석의 실제 ························································· 299

1) 질적 인자의 경우 299

2) 양적 인자의 경우 310

3) 분석 도구에 의한 분산분석 315

Chapter 13 이원배치 실험 ····························································· 318

1. 반복이 없는 이원배치 실험 ············································· 318

1) 실험 데이터의 분석 318

2) Excel에 의한 데이터의 분석 323

3) 분석 도구에 의한 분산분석 328

2. 반복이 있는 이원배치 실험 ············································· 331

1) 실험 데이터의 분석 331

2) Excel에 의한 데이터의 분석 334

3) 분석 도구에 의한 분산분석 345

Chapter 14 다원배치 실험 ····························································· 350

1. 3원배치 실험 ···································································· 350

1) 실험 데이터의 분석 350

2) Excel에 의한 데이터의 분석 355

2. 난괴법 ·············································································· 363

1) 실험 데이터의 분석 363

2) Excel에 의한 데이터의 분석 366

Chapter 15 비모수통계분석 ··························································· 369

1. 크러스컬－월리스의 순위검정 ·········································· 369

1) 실험 데이터의 분석 369

2) Excel에 의한 데이터의 분석 372

2. 프리드만의 순위검정 ······················································· 375

1) 실험 데이터의 분석 375

2) Excel에 의한 데이터의 분석 377

Chapter 16 직교배열 ······································································ 381

1. 직교배열표에 의한 실험의 계획 ······································ 381

1) 직교배열표의 이용 381

2) 할당의 실제 386

2. 직교배열 실험의 데이터 분석 ········································· 388

1) 분산분석의 방법 388

2) Excel에 의한 직교표 데이터의 분석 391

Chapter 17 다중비교 ······································································ 401

1. 최소유의차법 ···································································· 401

1) 최소유의차법의 실제 401

2) Excel에 의한 해법 404

2. Bonferroni법 ··································································· 407

1) Bonferroni법의 실제 407

2) Excel에 의한 해법 409

● 참고문헌 / 412

● Index / 414