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책소개이 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.
저자소개역자 : 장영순
명지대학교
역자 : 김도현
명지대학교
역자 : 권영훈
경남대학교
목차Chapter 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 |
| 교환 및 환불 가능 |
상품에 문제가 있을 경우 |
1) 상품이 표시/광고된 내용과 다르거나 불량(부패, 변질, 파손, 표기오류, 이물혼입, 중량미달)이 발생한 경우 - 신선식품, 냉장식품, 냉동식품 : 수령일 다음날까지 신청 - 기타 상품 : 수령일로부터 30일 이내, 그 사실을 안 날 또는 알 수 있었던 날로부터 30일 이내 신청 2) 교환 및 환불신청 시 판매자는 상품의 상태를 확인할 수 있는 사진을 요청할 수 있으며 상품의 문제 정도에 따라 재배송, 일부환불, 전체환불이 진행됩니다. 반품에 따른 비용은 판매자 부담이며 환불은 반품도착일로부터 영업일 기준 3일 이내에 완료됩니다. |
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단순변심 및 주문착오의 경우 |
1) 신선식품, 냉장식품, 냉동식품 재판매가 어려운 상품의 특성상, 교환 및 환불이 어렵습니다. 2) 화장품 피부 트러블 발생 시 전문의 진단서 및 소견서를 제출하시면 환불 가능합니다. 이 경우 제반비용은 소비자 부담이며, 배송비는 판매자가 부담합니다. 해당 화장품과 피부 트러블과의 상당한 인과관계가 인정되는 경우 또는 질환치료 목적의 경우에는 진단서 발급비용을 판매자가 부담합니다. 3) 기타 상품 수령일로부터 7일 이내 신청, 왕복배송비는 소비자 부담 4) 모니터 해상도의 차이로 색상이나 이미지가 다른 경우 단순변심에 의한 교환 및 환불이 제한될 수 있습니다. |
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| 교환 및 환불 불가 |
1) 신청기한이 지난 경우 2) 소비자의 과실로 인해 상품 및 구성품의 전체 또는 일부가 없어지거나 훼손, 오염되었을 경우 3) 개봉하여 이미 섭취하였거나 사용(착용 및 설치 포함)해 상품 및 구성품의 가치가 손상된 경우 4) 시간이 경과하여 상품의 가치가 현저히 감소한 경우 5) 상세정보 또는 사용설명서에 안내된 주의사항 및 보관방법을 지키지 않은 경우 6) 사전예약 또는 주문제작으로 통해 소비자의 주문에 따라 개별적으로 생산되는 상품이 이미 제작진행된 경우 7) 복제가 가능한 상품 등의 포장을 훼손한 경우 8) 맛, 향, 색 등 단순 기호차이에 의한 경우 |
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카테고리
