Modern business statistics with Microsoft Excel

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1. Verfasser: Anderson, David Ray 1941- (VerfasserIn)
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Veröffentlicht: Cincinnati, Ohio South-Western College Pub. 2003
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adam_text Chapter 1 Data and Statistics 1 Chapter 2 Descriptive Statistics: Tabular and Graphical Methods 26 Chapter 3 Descriptive Statistics: Numerical Methods 79 Chapter 4 Introduction to Probability 140 Chapter 5 Discrete Probability Distributions 184 Chapter 6 Continuous Probability Distributions 223 Chapter 7 Sampling and Sampling Distributions 254 Chapter 8 Interval Estimation 294 Chapter 9 Hypothesis Testing 335 Chapter 10 Statistical Inferences About Means and Proportions for Two Populations 397 Chapter 11 Inferences About Population Variances 446 Chapter 12 Tests of Goodness of Fit and Independence 473 Chapter 13 Analysis of Variance and Experimental Design 505 Chapter 14 Simple Linear Regression 564 Chapter 15 Multiple Regression 644 Chapter 16 Regression Analysis: Model Building 696 Chapter 17 Nonparametric Methods 748 Chapter 18 Sample Survery 789 Chapter 19 Statistical Methods for Quality Control 829 Appendix A References and Bibliography 863 Appendix B Tables 864 Appendix C Summation Notation 874 Appendix D Answers to Even Numbered Exercises 876 Appendix E Solutions to Self Test Exercises 893 Appendix F Excel Functions and the Function Wizard 924 Index 929 Chapter 1 Data and Statistics 1 Statistics in Practice: Business Week 2 1.1 Applications in Business and Economics 3 Accounting 3 Finance 3 Marketing 4 Production 4 Economics 4 1.2 Data 4 Elements, Variables, and Observations 5 Scales of Measurement 6 Qualitative and Quantitative Data 7 Cross Sectional and Time Series Data 7 1.3 Data Sources 8 Existing Sources 8 Statistical Studies 10 Data Acquisition Errors 11 1.4 Descriptive Statistics 12 1.5 Statistical Inference 14 1.6 Statistical Analysis Using Microsoft Excel 16 Data Sets and Excel Worksheets 16 Using Excel for Statistical Analysis 18 Summary 19 Glossary 20 Exercises 20 Chapter 2 Descriptive Statistics: Tabular and Graphical Methods 26 Statistics in Practice: Colgate Palmolive Company 27 2.1 Summarizing Qualitative Data 28 Frequency Distribution 28 Using Excel s COUNTIF Function to Construct a Frequency Distribution 29 Relative Frequency and Percent Frequency Distributions 29 Using Excel to Construct Relative Frequency and Percent Frequency Distributions 31 Bar Graphs and Pie Charts 32 Using Excel s Chart Wizard to Construct Bar Graphs and Pie Charts 33 Exercises 35 2.2 Summarizing Quantitative Data 37 Frequency Distribution 37 Using Excel s FREQUENCY Function to Construct a Frequency Distribution 39 Relative Frequency and Percent Frequency Distributions 40 Histogram 41 Using Excel s Chart Wizard to Construct a Histogram 42 Cumulative Distributions 43 Ogive 45 Exercises 47 2.3 Exploratory Data Analysis: The Stem and Leaf Display 50 Exercises 53 2.4 Crosstabulations and Scatter Diagrams 55 Crosstabulation 55 Using Excel s PivotTable Report to Construct a Crosstabulation 56 Scatter Diagram 60 Using Excel s Chart Wizard to Construct a Scatter Diagram 63 Exercises 64 Summary 67 Glossary 68 Key Formulas 69 Supplementary Exercises 69 Case Problem: Consolidated Foods 74 Appendix 2.1: Using Excel s Histogram Tool to Construct a Frequency Distribution and Histogram 75 Chapter 3 Descriptive Statistics: Numerical Methods 79 Statistics in Practice: Small Fry Design 80 3.1 Measures of Location 81 Mean 81 Median 82 Mode 83 Using Excel to Compute the Mean, Median, and Mode 84 Percentiles 85 Quartiles 86 Using Excel to Sort Data and Using Excel to Compute Percentiles and Quartiles 87 Exercises 88 3.2 Measures of Variability 92 Range 93 Interquartile Range 93 Variance 93 Standard Deviation 96 Using Excel to Compute the Sample Variance and Sample Standard Deviation 96 Coefficient of Variation 97 Using Excel s Descriptive Statistics Tool 98 Exercises 99 3.3 Measures of Relative Location and Detecting Outliers 101 z Scores 102 Chebyshev s Theorem 102 Empirical Rule 103 Detecting Outliers 104 Exercises 105 3.4 Exploratory Data Analysis 107 Five Number Summary 107 Box Plot 108 Exercises 109 3.5 Measures of Association Between Two Variables 112 Covariance 113 Interpretation of the Covariance 114 Correlation Coefficient 116 Interpretation of the Correlation Coefficient 117 Using Excel to Compute the Covariance and Correlation Coefficient 118 Exercises 119 3.6 The Weighted Mean and Working with Grouped Data 121 Weighted Mean 122 Grouped Data 123 Exercises 125 Summary 127 Glossary 128 Key Formulas 129 Supplementary Exercises 130 Case Problem 1: Consolidated Foods, Inc. 135 Case Problem 2: National Health Care Association 136 Case Problem 3: Business Schools of Asia Pacific 137 Chapter 4 Introduction to Probability 140 Statistics in Practice: Morton International 141 4.1 Experiments, Counting Rules, and Assigning Probabilities 142 Counting Rules, Combinations, and Permutations 143 Assigning Probabilities 147 Probabilities for the KP L Project 149 Exercises 150 4.2 Events and Their Probabilities 152 Exercises 154 4.3 Some Basic Relationships of Probability 156 Complement of an Event 156 Addition Law 157 Exercises 160 4.4 Conditional Probability 161 Independent Events 164 Multiplication Law 165 Exercises 166 4.5 Bayes Theorem 169 Tabular Approach 172 Using Excel to Compute Posterior Probabilities 173 Exercises 174 Summary 175 Glossary 176 Key Formulas 177 Supplementary Exercises 178 Case Problem: Hamilton County Judges 182 Chapter 5 Discrete Probability Distributions 184 Statistics in Practice: Citibank 185 5.1 Random Variables 185 Discrete Random Variables 186 Continuous Random Variables 187 Exercises 187 5.2 Discrete Probability Distributions 188 Exercises 191 5.3 Expected Value and Variance 193 Expected Value 193 Variance 194 Using Excel to Compute the Expected Value, Variance, and Standard Deviation 195 Exercises 196 5.4 Binomial Probability Distribution 199 A Binomial Experiment 199 Martin Clothing Store Problem 201 Using Excel to Compute Binomial Probabilities 205 Expected Value and Variance for the Binomial Probability Distribution 206 Exercises 207 5.5 Poisson Probability Distribution 209 An Example Involving Time Intervals 210 An Example Involving Length or Distance Intervals 211 Using Excel to Compute Poisson Probabilities 211 Exercises 213 5.6 Hypergeometric Probability Distribution 215 Using Excel to Compute Hypergeometric Probabilities 216 Exercises 216 Summary 217 Glossary 218 Key Formulas 219 Supplementary Exercises 220 Chapter 6 Continuous Probability Distributions 223 Statistics in Practice: Procter Gamble 224 6.1 Uniform Probability Distribution 225 Area as a Measure of Probability 226 Exercises 228 6.2 Normal Probability Distribution 229 Normal Curve 229 Standard Normal Probability Distribution 231 Computing Probabilities for Any Normal Probability Distribution 237 Grear Tire Company Problem 238 Using Excel to Compute Normal Probabilities 240 Exercises 243 6.3 Exponential Probability Distribution 245 Computing Probabilities for the Exponential Distribution 246 Relationship Between the Poisson and Exponential Distributions 247 Using Excel to Compute Exponential Probabilities 248 Exercises 249 Summary 250 Glossary 250 Key Formulas 251 Supplementary Exercises 251 Chapter 7 Sampling and Sampling Distributions 254 Statistics in Practice: Mead Corporation 255 7.1 The Electronics Associates Sampling Problem 256 7.2 Simple Random Sampling 257 Sampling from Finite Population 257 Using Excel to Select a Simple Random Sample 259 Sampling from Infinite Population 261 Exercises 262 7.3 Point Estimation 264 Exercises 266 7.4 Introduction to Sampling Distributions 267 7.5 Sampling Distributions of x 271 Expected Value of x 271 Standard Deviation of x 272 Central Limit Theorem 273 Sampling Distribution of x for the EAI Problem 275 Practical Value of the Sampling Distribution of x 276 Relationship Between the Sample Size and the Sampling Distribution of x 277 Exercises 279 7.6 Sampling Distribution of p 281 Expected Value of p 282 Standard Deviation of p 282 Form of the Sampling Distribution of p 283 Practical Value of the Sampling Distribution of p 284 Exercises 285 7.7 Other Sampling Methods 287 Stratified Random Sampling 287 Cluster Sampling 288 Systematic Sampling 288 Convenience Sampling 288 Judgment Sampling 289 Summary 289 Glossary 290 Key Formulas 291 Supplementary Exercises 291 Chapter 8 Interval Estimation 294 Statistics in Practice: Dollar General Corporation 295 8.1 Interval Estimation of a Population Mean: Large Sample Case 296 CJW Problem 296 Large Sample Case with o Assumed Known 298 Large Sample Case with a Estimated by s 300 Using Excel to Construct a Confidence Interval: Large Sample Case 302 Exercises 304 8.2 Interval Estimation of a Population Mean: Small Sample Case 306 Small Sample Case with a Assumed Known 306 Small Sample Case with a Estimated by s 307 Using Excel to Construct a Confidence Interval: With a Estimated bys 310 The Role of the Population Distribution 312 Exercises 315 8.3 Determining the Sample Size 317 Exercises 318 8.4 Interval Estimation of a Population Proportion 319 Using Excel to Construct a Confidence Interval 321 Determining the Sample Size 322 Exercises 324 Summary 326 Glossary 327 Key Formulas 327 Supplementary Exercises 328 Case Problem 1: Bock Investment Services 331 Case Problem 2: Gulf Real Estate Properties 331 Case Problem 3: Metropolitan Research, Inc. 334 Chapter 9 Hypothesis Testing 335 Statistics in Practice: Harris Corporation 336 9.1 Developing Null and Alternative Hypotheses 337 Testing Research Hypotheses 337 Testing the Validity of a Claim 337 Testing in Decision Making Situations 338 Summary of Forms for Null and Alternative Hypotheses 338 Exercises 339 9.2 Type I and Type H Errors 339 Exercises 341 9.3 One Tailed Tests About a Population Mean: Large Sample Case 342 One Tailed Tests: Large Sample Case with a Assumed Known 344 Use of p Values 346 Steps of Hypothesis Testing 347 One Tailed Tests: Large Sample Case with o Estimated by s 341 Using Excel to Conduct a One Tailed Hypothesis Test 349 Summary: One Tailed Tests About a Population Mean 352 Exercises 354 9.4 Two Tailed Tests About a Population Mean: Large Sample Case 356 p Values for Two Tailed Tests 357 Using Excel to Conduct a Two Tailed Hypothesis Test 358 Summary: Two Tailed Tests About a Population Mean 359 Relationship Between Interval Estimation and Hypothesis Testing 360 Exercises 362 9.5 Tests About a Population Mean: Small Sample Case 364 p Values and the t Distribution 366 Using Excel to Conduct a One Tailed Hypothesis Test: Small Sample Case 367 Two Tailed Test 369 Using Excel to Conduct a Two Tailed Hypothesis Test: Small Sample Case 369 Exercises 370 9.6 Tests About a Population Proportion 373 Using Excel to Conduct Hypothesis Tests About a Population Proportion 375 Exercises 378 9.7 Hypothesis Testing and Decision Making 380 9.8 Calculating the Probability of Type II Errors 381 Exercises 384 9.9 Determining the Sample Size for a Hypothesis Test About a Population Mean 385 Exercises 388 Summary 389 Glossary 391 Key Formulas 392 Supplementary Exercises 392 Case Problem 1: Unemployment Study 395 Case Problem 2: Quality Associates, Inc. 395 Chapter 10 Statistical Inferences About Means and Proportions for Two Populations 397 Statistics in Practice: Fisons Corporation 398 10.1 Estimation of the Difference Between the Means of Two Populations: Independent Samples 399 Sampling Distribution of xx — x2 401 Large Sample Case 401 Using Excel: Large Sample Case 403 Small Sample Case 404 Using Excel: Small Sample Case 407 Exercises 408 10.2 Hypothesis Tests About the Difference Between the Means of Two Populations: Independent Samples 411 Large Sample Case 411 Using Excel: Large Sample Case 414 Small Sample Case 416 Using Excel: Small Sample Case 418 Exercises 420 10.3 Inferences About the Difference Between the Means of Two Populations: Matched Samples 423 Using Excel 426 Exercises 428 10.4 Inferences About the Difference Between the Proportions of Two Populations 431 Sampling Distribution of px — p2 431 Interval Estimation of p, p2 432 Using Excel to Develop an Interval Estimate of px — p2 433 Hypothesis Tests About /?, — p2 434 Using Excel to Conduct a Hypothesis Test About px — p2 436 Exercises 437 Summary 439 Glossary 440 Key Formulas 440 Supplementary Exercises 442 Case Problem: Par, Inc. 444 Chapter 11 Inferences About Population Variances 446 Statistics in Practice: U.S. General Accounting Office 447 11.1 Inferences About a Population Variance 448 Interval Estimation of a2 448 Using Excel to Construct a Confidence Interval 452 Hypothesis Testing 453 Using Excel to Conduct a Hypothesis Test 457 Exercises 458 11.2 Inferences About the Variances of Two Populations 460 Using Excel to Conduct a Hypothesis Test 466 Exercises 467 Summary 469 Key Formulas 469 Supplementary Exercises 470 Case Problem: Air Force Training Program 471 Chapter 12 Tests of Goodness of Fit and Independence 473 Statistics in Practice: United Way 474 12.1 Goodness of Fit Test: A Multinomial Population 475 Using Excel to Conduct a Goodness of Fit Test 478 Exercises 479 12.2 Test of Independence 481 Using Excel to Conduct a Test of Independence 485 Exercises 486 12.3 Goodness of Fit Test: Poisson and Normal Distributions 489 Poisson Distribution 489 Using Excel to Conduct a Poisson Distribution Goodness of Fit Test 492 Normal Distribution 493 Using Excel to Conduct a Normal Distribution Goodness of Fit Test 497 Exercises 498 Summary 499 Glossary 499 Key Formulas 500 Supplementary Exercises 500 Case Problem: A Bipartisan Agenda for Change 503 Chapter 13 Analysis of Variance and Experimental Design 505 Statistics in Practice: Burke Marketing Services, Inc. 506 13.1 An Introduction to Analysis of Variance 506 Assumptions for Analysis of Variance 508 A Conceptual Overview 508 13.2 Analysis of Variance: Testing for the Equality of k Population Means 510 Between Treatments Estimate of Population Variance 512 Within Treatments Estimate of Population Variance 512 Comparing the Variance Estimates: The F Test 513 ANOVA Table 514 Using Excel s Anova: Single Factor Tool 515 Exercises 518 13.3 Multiple Comparison Procedures 521 Fisher s LSD 521 Type I Error Rates 523 Exercises 524 13.4 Introduction to Experimental Design 525 Data Collection 526 13.5 Completely Randomized Designs 528 Between Treatments Estimate of Population Variance 528 Within Treatments Estimate of Population Variance 529 Comparing the Variance Estimates: The F Test 529 ANOVA Table 530 Using Excel s Anova: Single Factor Tool 530 Pairwise Comparisons 530 Exercises 532 13.6 Randomized Block Design 534 Air Traffic Controller Stress Test 535 ANOVA Procedure 536 Computations and Conclusions 537 Using Excel s Anova: Two Factor Without Replication Tool 539 Exercises 540 13.7 Factorial Experiments 542 ANOVA Procedure 544 Computations and Conclusions 544 Using Excel s Anova: Two Factor With Replication Tool 547 Exercises 549 Summary 552 Glossary 552 Key Formulas 553 Supplementary Exercises 555 Case Problem 1: Wentworth Medical Center 561 Case Problem 2: Compensation for ID Professionals 562 Chapter 14 Simple Linear Regression 564 Statistics in Practice: Polaroid Corporation 565 14.1 Simple Linear Regression Model 566 Regression Model and Regression Equation 566 Estimated Regression Equation 567 14.2 Least Squares Method 568 Using Excel to Develop a Scatter Diagram and Compute the Estimated Regression Equation 573 Exercises 575 14.3 Coefficient of Determination 580 Using Excel to Compute the Coefficient of Determination 584 Correlation Coefficient 584 Exercises 586 14.4 Model Assumptions 588 14.5 Testing for Significance 590 Estimate of a2 590 fTest 591 Confidence Interval for /?[ 593 FTest 594 Some Cautions About the Interpretation of Significance Tests 596 Exercises 597 14.6 Excel s Regression Tool 599 Using Excel s Regression Tool for the Armand s Pizza Parlors Problem 599 Interpretation of Estimated Regression Equation Output 600 Interpretation of ANOVA Output 602 Interpretation of Regression Statistics Output 603 Exercises 603 14.7 Using the Estimated Regression Equation for Estimation and Prediction 606 Point Estimation 606 Interval Estimation 607 Confidence Interval Estimate of the Mean Value of y 607 Prediction Interval Estimate of an Individual Value of y 608 Using Excel to Develop Confidence and Prediction Interval Estimates 610 Exercises 612 14.8 Residual Analysis: Validating Model Assumptions 614 Residual Plot Against x 615 Using Excel s Regression Tool to Construct a Residual Plot 618 Standardized Residuals 618 Using Excel to Construct a Standardized Residual Plot 620 Normal Probability Plot 621 Exercises 623 14.9 Outliers and Influential Observations 625 Detecting Outliers 625 Detecting Influential Observations 626 Exercises 629 Summary 631 Glossary 631 Key Formulas 632 Supplementary Exercises 634 Case Problem 1: Spending and Student Achievement 639 Case Problem 2: U.S. Department of Transportation 641 Case Problem 3: Alumni Giving 642 Chapter 15 Multiple Regression 644 Statistics in Practice: Champion International Corporation 645 15.1 Multiple Regression Model 646 Regression Model and Regression Equation 646 Estimated Multiple Regression Equation 646 15.2 Least Squares Method 647 An Example: Butler Trucking Company 548 Using Excel s Regression Tool to Develop the Estimated Multiple Regression Equation 649 Note on Interpretation of Coefficients 652 Exercises 653 15.3 Multiple Coefficient of Determination 657 Exercises 658 15.4 Model Assumptions 660 15.5 Testing for Significance 661 FTest 661 fTest 664 Multicollinearity 665 Exercises 666 15.6 Using the Estimated Regression Equation for Estimation and Prediction 668 Exercises 669 15.7 Qualitative Independent Variables 670 An Example: Johnson Filtration, Inc. 670 Interpreting the Parameters 673 More Complex Qualitative Variables 674 Exercises 675 15.8 Residual Analysis 678 Residual Plot Against y 678 Standardized Residual Plot Against y 680 Exercises 681 Summary 682 Glossary 683 Key Formulas 684 Supplementary Exercises 684 Case Problem 1: Consumer Research, Inc. 690 Case Problem 2: NFL Quarterback Rating 691 Case Problem 3: Predicting Student Proficiency Test Scores 692 Case Problem 4: Alumni Giving 693 Chapter 16 Regression Analysis: Model Building 696 Statistics in Practice: Monsanto Company 697 16.1 General Linear Model 698 Modeling Curvilinear Relationships 698 Interaction 700 Transformations Involving the Dependent Variable 704 Nonlinear Models That Are Intrinsically Linear 707 Exercises 708 16.2 Determining When to Add or Delete Variables 711 General Case 713 | Use of p Values 714 | Exercises 715 j 16.3 Analysis of a Larger Problem 718 ! 16.4 Variable Selection Procedures 722 I Stepwise Regression 722 ; Forward Selection 723 i Backward Elimination 723 ! Using Excel to Perform the Backward Elimination Procedure 723 Best Subsets Regression 725 Exercises 726 16.5 Residual Analysis 728 Autocorrelation and the Durbin Watson Test 729 Exercises 734 16.6 Multiple Regression Approach to Analysis of Variance and Experimental Design 735 Exercises 738 Summary 739 Glossary 740 Key Formulas 740 Supplementary Exercises 740 Case Problem 1: Unemployment Study 744 Case Problem 2: Analysis of PGA Tour Statistics 745 Case Problem 3: Predicting Graduation Rates for Colleges and Universities 746 Chapter 17 Nonparametric Methods 748 i Statistics in Practice: West Shell Realtors 749 17.1 Sign Test 751 Small Sample Case 751 Using Excel 753 Large Sample Case 754 Using Excel 756 Hypothesis Test About a Median 756 Using Excel 757 Exercises 759 17.2 Wilcoxin Signed Rank Test 760 Using Excel 763 Exercises 764 17.3 Mann Whitney Wilcoxin Test 766 Small Sample Case 767 Large Sample Case 769 ! Using Excel 772 Exercises 772 17.4 Kruskal Wallis Test 775 Using Excel 777 Exercises 778 17.5 Rank Correlation 780 Test for Significant Rank Correlation 780 Using Excel 782 Exercises 783 Summary 785 Glossary 785 Key Formulas 786 Supplementary Exercises 786 Chapter 18 Sample Survey 789 Statistics in Practice: Cinergy 790 18.1 Terminology Used in Sample Surveys 790 18.2 Types of Surveys and Sampling Methods 791 18.3 Survey Errors 793 Nonsampling Error 793 Sampling Error 793 18.4 Simple Random Sampling 794 Population Mean 794 Population Total 795 Population Proportion 797 Using Excel for Simple Random Sampling 797 Determining the Sample Size 799 Exercises 802 18.5 Stratified Simple Random Sampling 802 Population Mean 803 Using Excel: Population Mean 805 Population Total 806 Using Excel: Population Total 807 Population Proportion 807 Using Excel: Population Proportion 809 Determining the Sample Size 809 Exercises 812 18.6 Cluster Sampling 813 Population Mean 815 Population Total 817 Population Proportion 817 Using Excel for Cluster Sampling 819 Determining the Sample Size 819 Exercises 819 18.7 Systematic Sampling 821 Summary 821 Glossary 822 Key Formulas 823 Supplementary Exercises 826 Chapter 19 Statistical Methods for Quality Control 829 Statistics in Practice: Dow Chemical 830 19.1 Statistical Process Control 831 Control Charts 832 x Chart: Process Mean and Standard Deviation Known 833 I x Chart: Process Mean and Standard Deviation Unknown 835 R Chart 838 Using Excel to Construct an R Chart and an x Chart 840 p Chart 843 np Chart 845 Interpretation of Control Charts 846 Exercises 846 19.2 Acceptance Sampling 848 KALI, Inc.: An Example of Acceptance Sampling 850 Computing the Probability of Accepting a Lot 850 Selecting an Acceptance Sampling Plan 852 Multiple Sampling Plans 854 Exercises 856 Summary 857 Glossary 857 Key Formulas 858 Supplementary Exercises 859 Appendix A References and Bibliography 863 Appendix B Tables 864 Appendix C Summation Notation 874 Appendix D Answers to Even Numbered Exercises 876 Appendix E Solutions to Self Test Exercises 893 Appendix F Excel Functions and the Function Wizard 924 Index 929
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genre_facet Einführung
id DE-604.BV014398199
illustrated Illustrated
index_date 2024-09-19T15:17:20Z
indexdate 2024-09-27T16:12:33Z
institution BVB
isbn 0324121741
language English
lccn 2001049276
oai_aleph_id oai:aleph.bib-bvb.de:BVB01-009853523
oclc_num 144599401
open_access_boolean
owner DE-473
DE-BY-UBG
owner_facet DE-473
DE-BY-UBG
physical XXIII, 936 S. Ill., graph. Darst. 1 CD-ROM (12 cm)
publishDate 2003
publishDateSearch 2003
publishDateSort 2003
publisher South-Western College Pub.
record_format marc
spellingShingle Anderson, David Ray 1941-
Modern business statistics with Microsoft Excel
Microsoft Excel for Windows
Commercial statistics
Betriebsstatistik (DE-588)4006211-9 gnd
EXCEL (DE-588)4138932-3 gnd
Deskriptive Statistik (DE-588)4070313-7 gnd
Inferenzstatistik (DE-588)4247120-5 gnd
subject_GND (DE-588)4006211-9
(DE-588)4138932-3
(DE-588)4070313-7
(DE-588)4247120-5
(DE-588)4151278-9
title Modern business statistics with Microsoft Excel
title_alt Microsoft Excel data files
title_auth Modern business statistics with Microsoft Excel
title_exact_search Modern business statistics with Microsoft Excel
title_full Modern business statistics with Microsoft Excel David R. Anderson, Dennis J. Sweeney, Thomas A. Williams
title_fullStr Modern business statistics with Microsoft Excel David R. Anderson, Dennis J. Sweeney, Thomas A. Williams
title_full_unstemmed Modern business statistics with Microsoft Excel David R. Anderson, Dennis J. Sweeney, Thomas A. Williams
title_short Modern business statistics with Microsoft Excel
title_sort modern business statistics with microsoft excel
topic Microsoft Excel for Windows
Commercial statistics
Betriebsstatistik (DE-588)4006211-9 gnd
EXCEL (DE-588)4138932-3 gnd
Deskriptive Statistik (DE-588)4070313-7 gnd
Inferenzstatistik (DE-588)4247120-5 gnd
topic_facet Microsoft Excel for Windows
Commercial statistics
Betriebsstatistik
EXCEL
Deskriptive Statistik
Inferenzstatistik
Einführung
url http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009853523&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
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