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.

역자 : 유태종 유태종(상명대학교) 역자 : 이근철 이근철(건국대학교) 역자 : 허정 허 정(한경대학교) 역자 : 황윤민 황윤민(충북대학교) 역자 : 장영순 명지대학교 역자 : 김도현 명지대학교 역자 : 권영훈 경남대학교 역자 : 김옹규 김옹규(한밭대학교) 역자 : 박진한 박진한(경남대학교) 역자 : 서종현 서종현(한국산업기술대학교)

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