앤더슨의 경영통계학(8판)
Regular price
$43.82
Sale price
Regular price
Shipping calculated at checkout.
✈️
Estimated delivery date 예상 배송일
Standard Shipping
불러오는 중...
주문일로부터 8-12 영업일
Express Shipping
불러오는 중...
주문일로부터 6-8 영업일
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.
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.
Couldn't load pickup availability
출판사 리뷰
출판사 리뷰
목차
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································································34
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································································34
저자
저자
Anderson
Payment & Security
Payment methods
Your payment information is processed securely. We do not store credit card details nor have access to your credit card information.
