Verfügbarkeit: Business statistics

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Bibliographische Detailangaben
Hauptverfasser:	Sharpe, Norean R. (VerfasserIn), De Veaux, Richard D. (VerfasserIn), Velleman, Paul F. (VerfasserIn)
Format:	Buch
Sprache:	English
Veröffentlicht:	New York ; Munich [u.a.] Pearson Education International 2010
Ausgabe:	Internat. ed.
Schlagworte:	Betriebsstatistik Statistische Methodenlehre Commercial statistics Betriebswirtschaftliche Statistik Lehrbuch
Online-Zugang:	Inhaltsverzeichnis Inhaltsverzeichnis
Beschreibung:	XL, 762, 70 S. Ill., graph. Darst. 1 CD-ROM (12 cm)
ISBN:	0321615972 9780321615978 032150688X

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Datensatz im Suchindex

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adam_text	: : : 5 V -T)I.- :/. .-,, .. BUSINESS STATISTICS NOREAN R. SHARPE BABSON COLLEGE RICHARD D. DE VEAUX WILLIAMS COLLEGE PAUL F. VELLEMAN CORNELL UNIVERSITY .USON I ILIU.ITION INTERN ITION IL MEXICO CIP PIRR. F ]))* LIMN I [ON, KMV MI CONTENTS PREFACE XIX PART I EXPLORING AND COLLECTING DATA 1 CHAPTER 1 CHAPTER 2 STATISTICS AND VARIATION 3 SO, WHAT IS STATISTICS? * HOW WILL THIS BOOK HELP? DATA 9 2.1 WHAT/4N?DATA? * 2.2 VARIABLE TYPES * 2.3 WHERE, HOW, AND WHEN MINI CASE STUDY PROJECT: CREDIT CARD BANK 22 CHAPTER 3 27 SURVEYS AND SAMPLING 3.1 THREE IDEAS OF SAMPLING * 3.2 A CENSUSDOES IT MAKE SENSE? 3.3 POPULATIONS AND PARAMETERS E 3.4 SIMPLE RANDOM SAMPLE (SRS) * 3.5 OTHER SAMPLE DESIGNS * 3.6 DEFINING THE POPULATION * 3.7 THE VALID SURVEY MINI CASE STUDY PROJECTS: MARKET SURVEY RESEARCH 47, THE GFK ROPER REPORTS WORLDWIDE SURVEY 47 CHAPTER 4 DISPLAYING AND DESCRIBING CATEGORICAL DATA 53 4.1 THE THREE RULES OF DATA ANALYSIS * 4.2 FREQUENCY TABLES * 4.3 CHARTS * 4.4 CONTINGENCY TABLES MINI CASE STUDY PROJECT: KEEN FOOTWEAR 74 VLL VLLL CONTENTS CHAPTER 5 RANDOMNESS AND PROBABILITY 85 5.1 RANDOM PHENOMENA AND PROBABILITY * 5.2 THE NONEXIS- TENT LAW OF AVERAGES 8 5.3 DIFFERENT TYPES OF PROBABILITY * 5.4 PROBABILITY RULES 8 5.5 JOINT PROBABILITY AND CONTINGENCY TABLES 8 5.6 CONDITIONAL PROBABILITY * 5.7 CONSTRUCTING CONTINGENCY TABLES MINI CASE STUDY PROJECT: MARKET SEGMENTATION 103 CHAPTER 6 DISPLAYING AND DESCRIBING QUANTITATIVE DATA IN 6.1 DISPLAYING DISTRIBUTIONS 8 6.2 SHAPE * 6.3 CENTER * I 6.4 SPREAD OF THE DISTRIBUTION 8 6.5 SHAPE, CENTER, AND SPREADA SUMMARY 6.6 FIVE-NUMBER SUMMARY AND BOXPLOTS E 6.7 COMPARING GROUPS * 6.8 IDENTIFYING OUTLIERS * 6.9 STANDARDIZING 8 6.10 TIME SERIES PLOTS 8 6.11 TRANSFORMING SKEWED DATA MINI CASE STUDY PROJECTS: HOTEL OCCUPANCY RATES 143, VALUE AND GROWTH STOCK RETURNS 143 PART II UNDERSTANDING DATA AND DISTRIBUTIONS 157 CHAPTER 7 SCATTERPLOTS, ASSOCIATION, AND CORRELATION 159 7.1 LOOKING AT SCATTERPLOTS 7.2 ASSIGNING ROLES TO VARIABLES IN SCATTERPLOTS 8 7.3 UNDERSTANDING CORRELATION 8 7.4 STRAIGHTENING SCATTERPLOTS 8 7.5 LURKING VARIABLES AND CAUSATION MINI CASE STUDY PROJECTS: FUEL EFFICIENCY 181, THE U.S. ECONOMY AND HOME DEPOT STOCK PRICES 182 CHAPTER 8 LINEAR REGRESSION 193 8.1 THE LINEAR MODEL S 8.2 CORRELATION AND THE LINE 8 8.3 REGRESSION TO THE MEAN 8 8.4 CHECKING THE MODEL * 8.5 LEARNING MORE FROM THE RESIDUALS 8.6 VARIATION IN THE MODEL AND R 2 * 8.7 REALITY CHECK: IS THE REGRES- SION REASONABLE? MINI CASE STUDY PROJECTS: COST OF LIVING 213, MUTUAL FUNDS 213 CHAPTER 9 SAMPLING DISTRIBUTIONS AND THE NORMAL MODEL 223 9.1 MODELING THE DISTRIBUTION OF SAMPLE PROPORTIONS 8 9.2 SIMULATIONS * 9.3 THE NORMAL DISTRIBUTION 8 9.4 PRACTICE WITH NORMAL DISTRIBUTION CALCULATIONS 8 9.5 THE SAMPLING DISTRIBUTION FOR PROPORTIONS * 9.6 ASSUMPTIONS AND CONDITIONS * 9.7 THE CENTRAL LIMIT THEOREMTHE FUNDAMENTAL THEOREM OF STATISTICS 8 9.8 THE SAMPLING DISTRIBUTION OF THE MEAN 9.9 SAMPLE SIZEDIMINISHING RETURNS 9.10 HOW SAMPLING DISTRIBUTION MODELS WORK MINI CASE STUDY PROJECT: REAL ESTATE SIMULATION 247 INDICATES AN OPTIONAL TOPIC CONTENTS IX CHAPTER 10 CONFIDENCE INTERVALS FOR PROPORTIONS 255 10.1 A CONFIDENCE INTERVAL 10.2 MARGIN OF ERROR: CERTAINTY VS. PRECISION * 10.3 CRITICAL VALUES * 10.4 ASSUMPTIONS AND CONDITIONS 8 10.5 A CONFIDENCE INTERVAL FOR SMALL SAMPLES 10.6 CHOOSING THE SAMPLE SIZE MINI CASE STUDY PROJECTS: INVESTMENT 272, FORECASTING DEMAND 272 CHAPTER 11 TESTING HYPOTHESES ABOUT PROPORTIONS 279 11.1 HYPOTHESES 8 11.2 A TRIAL AS A HYPOTHESIS TEST 8 11.3 P-VALUES S 11.4 THE REASONING OF HYPOTHESIS TESTING * 11.5 ALTERNATIVE HYPOTHESES 8 11.6 ALPHA LEVELS AND SIGNIFICANCE 8 11.7 CRITICAL VALUES 8 11.8 CONFIDENCE INTERVALS AND HYPOTHESIS TESTS 8 11.9 TWO TYPES OF ERRORS 8 11.10 POWER MINI CASE STUDY PROJECTS: METAL PRODUCTION 305, LOYALTY PROGRAM 305 CHAPTER 12 CONFIDENCE INTERVALS AND HYPOTHESIS TESTS FOR MEANS 313 12.1 THE SAMPLING DISTRIBUTION FOR THE MEAN 8 12.2 A CONFIDENCE INTERVAL FOR MEANS 8 12.3 ASSUMPTIONS AND CONDITIONS 12.4 CAUTIONS ABOUT INTERPRETING CONFIDENCE INTERVALS 8 12.5 ONE-SAMPLE ?-TEST 8 12.6 SAMPLE SIZE * 12.7 DEGREES OF FREEDOMWHYW-1? MINI CASE STUDY PROJECTS: REAL ESTATE 333, DONOR PROFILES 333 CHAPTER 13 COMPARING TWO MEANS 343 13.1 TESTING DIFFERENCES BETWEEN TWO MEANS 8 13.2 THE TWO-SAMPLE ?-TEST * 13.3 ASSUMPTIONS AND CONDITIONS * 13.4 A CONFIDENCE INTERVAL FOR THE DIFFERENCE BETWEEN TWO MEANS 8 13.5 THE POOLED ^-TEST 8 13.6 TUKEY S QUICK TEST MINI CASE STUDY PROJECT: REAL ESTATE 364 CHAPTER 14 PAIRED SAMPLES AND BLOCKS 375 14.1 PAIRED DATA 14.2 ASSUMPTIONS AND CONDITIONS 8 14.3 THE PAIRED -TEST 8 14.4 HOW THE PAIRED T-TEST WORKS MINI CASE STUDY PROJECTS: A TASTE TEST (DATA COLLECTION AND ANALYSIS) 389, CONSUMER SPENDING PATTERNS (DATA ANALYSIS) 389 CHAPTER 15 INFERENCE FOR COUNTS: CHI-SQUARE TESTS 401 15.1 GOODNESS-OF-FIT TESTS 8 15.2 INTERPRETING CHI-SQUARE VALUES 8 15.3 EXAMINING THE RESIDUALS 8 15.4 THE CHI- SQUARE TEST OF HOMOGENEITY 8 15.5 COMPARING TWO PROPORTIONS E 15.6 CHI-SQUARE TEST OF INDEPENDENCE MINI CASE STUDY PROJECTS: HEALTH INSURANCE 424, LOYALTY PROGRAM 424 CONTENTS PART III EXPLORING RELATIONSHIPS AMONG VARIABLES 435 CHAPTER 16 INFERENCE FOR REGRESSION 437 16.1 THE POPULATION AND THE SAMPLE * 16.2 ASSUMPTIONS AND CONDITIONS 8 16.3 THE STANDARD ERROR OF THE SLOPE * 16.4 A TEST FOR THE REGRESSION SLOPE * 16.5 A HYPOTHESIS TEST FOR CORRELATION * 16.6 STANDARD ERRORS FOR PREDICTED VALUES 8 16.7 USING CONFIDENCE AND PREDICTION INTERVALS MINI CASE STUDY PROJECTS: FROZEN PIZZA 461, GLOBAL WARMING? 461 CHAPTER 17 UNDERSTANDING RESIDUALS 473 17.1 EXAMINING RESIDUALS FOR GROUPS 8 17.2 EXTRAPOLATION AND PREDICTION S 17.3 UNUSUAL AND EXTRAORDINARY -- OBSERVATIONS 6 17.4 WORKING WITH SUMMARY VALUES 8 17.5 AUTOCORRELATION E 17.6 LINEARITY 8 17.7 TRANSFORMING (RE-EXPRESSING) DATA * 17.8 THE LADDER OF POWERS MINI CASE STUDY PROJECTS: GROSS DOMESTIC PRODUCT 497, ENERGY SOURCES 498 CHAPTER 18 MULTIPLE REGRESSION 509 18.1 THE MULTIPLE REGRESSION MODEL * 18.2 INTERPRETING MULTIPLE REGRESSION COEFFICIENTS * 18.3 ASSUMPTIONS AND CONDITIONS FOR THE MULTIPLE REGRESSION MODEL 8 18.4 TESTING THE MULTIPLE REGRESSION MODEL 8 18.5 ADJUSTED R 2 , AND THE F-STATISTIC * * 18.6 THE LOGISTIC REGRESSION MODEL MINI CASE STUDY PROJECT: GOLF SUCCESS 536 CHAPTER 19 BUILDING MULTIPLE REGRESSION MODELS 547 19.1 INDICATOR (OR DUMMY) VARIABLES * 19.2 ADJUSTING FOR DIFFERENT SLOPESINTERACTION TERMS 19.3 MULTIPLE REGRESSION DIAGNOSTICS * 19.4 BUILDING REGRESSION MODELS * 19.5 COLLINEARITY * 19.6 QUADRATIC TERMS MINI CASE STUDY PROJECT: PARALYZED VETERANS OF AMERICA 577 CHAPTER 20 TIME SERIES ANALYSIS 589 20.1 WHAT IS A TIME SERIES? * 20.2 COMPONENTS OF A TIME SERIES 8 20.3 SMOOTHING METHODS * 20.4 SIMPLE MOVING AVERAGE METHODS 8 20.5 WEIGHTED MOVING AVERAGES * 20.6 EXPONENTIAL SMOOTHING METHODS 8 20.7 SUMMARIZING FORECAST ERROR * 20.8 AUTOREGRESSIVE MODELS * 20.9 RANDOM WALKS 8 20.10 MULTIPLE REGRESSION-BASED MODELS * 20.11 ADDITIVE AND MULTIPLICATIVE MODELS * 20.12 CYCLICAL AND IRREGULAR COMPONENTS 8 20.13 FORECASTING WITH REGRESSION- BASED MODELS * 20.14 CHOOSING A TIME SERIES FORECASTING METHOD * 20.15 INTERPRETING TIME SERIES MODELS: THE WHOLE FOODS DATA REVISITED MINI CASE STUDY PROJECTS: INTEL CORPORATION 624, TIFFANY & CO. 624 CONTENTS XI PART IV BUILDING MODELS FOR DECISION MAKING 637 CHAPTER 21 RANDOM VARIABLES AND PROBABILITY MODELS 639 21.1 EXPECTED VALUE OF A RANDOM VARIABLE 8 21.2 STANDARD DEVIATION OF A RANDOM VARIABLE 8 21.3 PROPERTIES OF EXPECTED VALUES AND VARIANCES 21 A DISCRETE PROBABILITY MODELS 8 21.5 CONTINUOUS RANDOM VARIABLES MINI CASE STUDY PROJECT: INVESTMENT OPTIONS 668 CHAPTER 22 DECISION MAKING AND RISK 675 22.1 ACTIONS, STATES OF NATURE, AND OUTCOMES 22.2 PAYOFF TABLES AND DECISION TREES 8 22.3 MINIMIZING LOSS AND MAXIMIZING GAIN * 22.4 THE EXPECTED VALUE OF AN ACTION 8 22.5 EXPECTED VALUE WITH PERFECT INFORMATION 8 22.6 DECISIONS MADE WITH SAMPLE INFORMATION * 22.7 ESTIMATING VARIATION * 22.8 SENSITIVITY 8 22.9 SIMULATION * 22.10 PROBABILITY TREES * 22.11 REVERSING THE CONDITIONING: BAYES S RULE 8 22.12 MORE COMPLEX DECISIONS MINI CASE STUDY PROJECTS: TEXACO-PENNZOIL 693, INSURANCE SERVICES, REVISITED 694 CHAPTER 23 DESIGN AND ANALYSIS OF EXPERIMENTS AND OBSERVATIONAL STUDIES 699 23.1 OBSERVATIONAL STUDIES 23.2 RANDOMIZED, COMPARATIVE EXPERIMENTS * 23.3 THE FOUR PRINCIPLES OF EXPERIMENTAL DESIGN * 23.4 EXPERIMENTAL DESIGNS 8 23.5 BLINDIN G AND PLACEBOS * 23.6 CONFOUNDING AND LURKING VARIABLES 8 23.7 ANALYZING A DESIGN IN ONE FACTORTHE ANALYSIS OF VARIANCE 23.8 ASSUMPTIONS AND CONDITIONS FOR ANOVA 8 2 3.9 MULTIPLE COMPARISONS 8 23.10 ANOVA ON OBSERVATIONAL DATA 23.11 ANALYSIS OF MULTIFACTOR DESIGNS MINI CASE STUDY PROJECT: A MULTIFACTOR EXPERIMENT 736 CHAPTER 24 INTRODUCTION TO DATA MINING 747 24.1 DIRECT MARKETING 8 24.2 THE DATA 8 24.3 THE GOALS OF DATA MINING 8 24.4 DATA MINING MYTHS 8 24.5 SUCCESSFUL DATA MINING 8 24.6 DATA MINING PROBLEMS 8 24.7 DATA MINING ALGORITHMS 8 24.8 THE DATA MINING PROCESS 8 24.9 SUMMARY APPENDIXES A ANSWERS A-L B PHOTO ACKNOWLEDGMENTS A-37 C TABLES AND SELECTED FORMULAS A-41 D INDEX A-57
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spelling	Sharpe, Norean R. Verfasser (DE-588)138105413 aut Business statistics Norean R. Sharpe ; Richard D. De Veaux ; Paul F. Velleman Internat. ed. New York ; Munich [u.a.] Pearson Education International 2010 XL, 762, 70 S. Ill., graph. Darst. 1 CD-ROM (12 cm) txt rdacontent n rdamedia nc rdacarrier Betriebsstatistik stw Statistische Methodenlehre stw Commercial statistics Betriebswirtschaftliche Statistik (DE-588)4006243-0 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Betriebswirtschaftliche Statistik (DE-588)4006243-0 s DE-604 De Veaux, Richard D. Verfasser (DE-588)138105170 aut Velleman, Paul F. Verfasser aut DE-601 pdf/application http://www.gbv.de/dms/zbw/593153286.pdf kostenfrei Inhaltsverzeichnis GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017544449&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis
spellingShingle	Sharpe, Norean R. De Veaux, Richard D. Velleman, Paul F. Business statistics Betriebsstatistik stw Statistische Methodenlehre stw Commercial statistics Betriebswirtschaftliche Statistik (DE-588)4006243-0 gnd
subject_GND	(DE-588)4006243-0 (DE-588)4123623-3
title	Business statistics
title_auth	Business statistics
title_exact_search	Business statistics
title_full	Business statistics Norean R. Sharpe ; Richard D. De Veaux ; Paul F. Velleman
title_fullStr	Business statistics Norean R. Sharpe ; Richard D. De Veaux ; Paul F. Velleman
title_full_unstemmed	Business statistics Norean R. Sharpe ; Richard D. De Veaux ; Paul F. Velleman
title_short	Business statistics
title_sort	business statistics
topic	Betriebsstatistik stw Statistische Methodenlehre stw Commercial statistics Betriebswirtschaftliche Statistik (DE-588)4006243-0 gnd
topic_facet	Betriebsstatistik Statistische Methodenlehre Commercial statistics Betriebswirtschaftliche Statistik Lehrbuch
url	http://www.gbv.de/dms/zbw/593153286.pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=017544449&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
work_keys_str_mv	AT sharpenoreanr businessstatistics AT deveauxrichardd businessstatistics AT vellemanpaulf businessstatistics

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