Book Cover
Author Anderson, David R. (David Ray), 1941-

Title Contemporary business statistics with Microsoft Excel / David R. Anderson, Dennis J. Sweeney, Thomas A. Williams
Published Cincinnati, Ohio : South-Western College Pub., [2001]
Table of Contents
 About the Authorsxx
Chapter 1Data and Statistics1
  Statistics in Practice: Business Week2
 1.1Applications in Business and Economics3
   Elements, Variables, and Observations5
   Qualitative and Quantitative Data6
   Cross-Sectional and Time Series Data7
 1.3Data Sources7
   Existing Sources7
   Statistical Studies10
   Data Acquisition Errors11
 1.4Descriptive Statistics12
 1.5Statistical Inference14
 1.6Statistical Analysis Using Microsoft Excel15
   Data Sets and Excel Worksheets16
   Using Excel for Statistical Analysis17
Chapter 2Descriptive Statistics: Tabular and Graphical Methods25
  Statistics in Practice: Colgate-Palmolive Company26
 2.1Summarizing Qualitative Data27
   Frequency Distribution27
   Using Excel's COUNTIF Function to Construct a Frequency Distribution28
   Relative Frequency and Percent Frequency Distributions28
   Using Excel to Construct Relative Frequency and Percent Frequency Distributions30
   Bar Graphs and Pie Charts30
   Using Excel's Chart Wizard to Construct Bar Graphs and Pie Charts32
 2.2Summarizing Quantitative Data37
   Frequency Distribution37
   Using Excel's FREQUENCY Function to Construct a Frequency Distribution38
   Relative Frequency and Percent Frequency Distributions40
   Using Excel's Chart Wizard to Construct a Histogram41
   Cumulative Distributions42
 2.3Exploratory Data Analysis: The Stem-and-Leaf Display49
 2.4Crosstabulations and Scatter Diagrams54
   Using Excel's PivotTable Report to Construct a Crosstabulation56
   Scatter Diagram60
   Using Excel's Chart Wizard to Construct a Scatter Diagram61
  Key Formulas67
  Supplementary Exercises68
  Case Problem: Consolidated Foods73
 Appendix 2.1Using Excel's Histogram Tool to Construct a Frequency Distribution and Histogram74
Chapter 3Descriptive Statistics: Numerical Methods78
  Statistics in Practice: Small Fry Design79
 3.1Measures of Location80
   Using Excel to Compute the Mean, Median, and Mode83
   Sorting Data and Using Excel to Compute Percentiles and Quartiles87
 3.2Measures of Variability91
   Interquartile Range92
   Standard Deviation94
   Using Excel to Compute the Sample Variance and Sample Standard Deviation95
   Coefficient of Variation96
   Using Excel's Descriptive Statistics Tool97
 3.3Measures of Relative Location and Detecting Outliers101
   Chebyshev's Theorem102
   Empirical Rule103
   Detecting Outliers104
 3.4Exploratory Data Analysis106
   Five-Number Summary106
   Box Plot107
 3.5Measures of Association between Two Variables110
   Interpretation of the Covariance113
   Correlation Coefficient115
   Interpretation of the Correlation Coefficient116
   Using Excel to Compute the Covariance and Correlation Coefficient117
 3.6The Weighted Mean and Working with Grouped Data120
   Weighted Mean121
   Grouped Data122
  Key Formulas128
  Supplementary Exercises129
 Case Problem 1Consolidated Foods, Inc.132
 Case Problem 2National Health Care Association133
 Case Problem 3Business Schools of Asia-Pacific134
Chapter 4Introduction to Probability137
  Statistics in Practice: Morton International138
 4.1Experiments, Counting Rules, and Assigning Probabilities139
   Counting Rules, Combinations, and Permutations140
   Assigning Probabilities144
   Probabilities for the KP&L Project146
 4.2Events and Their Probabilities149
 4.3Some Basic Relationships of Probability153
   Complement of an Event153
   Addition Law154
 4.4Conditional Probability158
   Independent Events162
   Multiplication Law162
 4.5Bayes' Theorem166
   Tabular Approach170
   Using Excel to Compute Posterior Probabilities170
  Key Formulas174
  Supplementary Exercises175
  Case Problem: Hamilton County Judges179
Chapter 5Discrete Probability Distributions181
  Statistics in Practice: Citibank182
 5.1Random Variables183
   Discrete Random Variables183
   Continuous Random Variables183
 5.2Discrete Probability Distributions186
 5.3Expected Value and Variance191
   Expected Value191
   Using Excel to Compute the Expected Value, Variance, and Standard Deviation192
 5.4Binomial Probability Distribution196
   A Binomial Experiment197
   Martin Clothing Store Problem198
   Using Excel to Compute Binomial Probabilities202
   Expected Value and Variance for the Binomial Probability Distribution204
 5.5Poisson Probability Distribution207
   An Example Involving Time Intervals208
   An Example Involving Length or Distance Intervals208
   Using Excel to Compute Poisson Probabilities209
 5.6Hypergeometric Probability Distribution212
   Using Excel to Compute Hypergeometric Probabilities214
  Key Formulas216
  Supplementary Exercises217
Chapter 6Continuous Probability Distributions220
  Statistics in Practice: Procter & Gamble221
 6.1Uniform Probability Distribution222
   Area as a Measure of Probability223
 6.2Normal Probability Distribution226
   Normal Curve227
   Standard Normal Probability Distribution229
   Computing Probabilities for Any Normal Probability Distribution234
   Grear Tire Company Problem235
   Using Excel to Compute Normal Probabilities237
 6.3Exponential Probability Distribution242
   Computing Probabilities for the Exponential Distribution243
   Relationship between the Poisson and Exponential Distributions244
   Using Excel to Compute the Exponential Probabilities245
  Key Formulas248
  Supplementary Exercises248
Chapter 7Sampling and Sampling Distributions251
  Statistics in Practice: Mead Corporation252
 7.1The Electronics Associates Sampling Problem253
 7.2Simple Random Sampling254
   Sampling from Finite Populations254
   Using Excel to Select a Simple Random Sample256
   Sampling from Infinite Populations258
 7.3Point Estimation261
 7.4Introduction to Sampling Distributions264
 7.5Sampling Distribution of x267
   Expected Value of x268
   Standard Deviation of x268
   Central Limit Theorem270
   Sampling Distribution of x for the EAI Problem272
   Practical Value of the Sampling Distribution of x272
   Relationship between the Sample Size and the Sampling Distribution of x274
 7.6Sampling Distribution of p278
   Expected Value of p278
   Standard Deviation of p278
   Form of the Sampling Distribution of p279
   Practical Value of the Sampling Distribution of p280
 7.7Other Sampling Methods283
   Stratified Random Sampling283
   Cluster Sampling284
   Systematic Sampling284
   Convenience Sampling285
   Judgment Sampling285
  Key Formulas287
  Supplementary Exercises288
Chapter 8Interval Estimation290
  Statistics in Practice: Dollar General Corporation291
 8.1Interval Estimation of a Population Mean: Large-Sample Case292
   CJW Problem292
   Sampling Error293
   Constructing an Interval Estimate294
   Interpreting an Interval Estimate294
   The General Procedure296
   Constructing an Interval Estimate: Large-Sample Case with [sigma] Unknown297
   Using Excel to Construct a Confidence Interval: [sigma] Unknown298
 8.2Interval Estimation of a Population Mean: Small-Sample Case301
   Using Excel to Construct a Confidence Interval: [sigma] Unknown305
 8.3Determining the Sample Size309
 8.4Interval Estimation of a Population Proportion312
   Using Excel to Construct a Confidence Interval313
   Determining the Sample Size314
  Key Formulas320
  Supplementary Exercises320
 Case Problem 1Bock Investment Services323
 Case Problem 2Metropolitan Research, Inc.323
Chapter 9Hypothesis Testing326
  Statistics in Practice: Harris Corporation327
 9.1Developing Null and Alternative Hypotheses328
   Testing Research Hypotheses328
   Testing the Validity of a Claim328
   Testing in Decision-Making Situations329
   Summary of Forms for Null and Alternative Hypotheses329
 9.2Type I and Type II Errors330
 9.3One-Tailed Tests about a Population Mean: Large-Sample Case333
   Use of p-Values337
   Steps of Hypothesis Testing338
   One-Tailed Tests: Large-Sample Case with [sigma] Unknown338
   Using Excel to Conduct a One-Tailed Hypothesis Test340
   Summary: One-Tailed Test about a Population Mean342
 9.4Two-Tailed Tests about a Population Mean: Large-Sample Case345
   p-Values for Two-Tailed Tests347
   Using Excel to Conduct a Two-Tailed Hypothesis Test348
   Summary: Two-Tailed Tests about a Population Mean349
   Relationship between Interval Estimation and Hypothesis Testing350
 9.5Tests about a Population Mean: Small-Sample Case354
   p-Values and the t Distribution355
   Using Excel to Conduct a One-Tailed Hypothesis Test: Small-Sample Case356
   A Two-Tailed Test358
   Using Excel to Conduct a Two-Tailed Hypothesis Test: Small-Sample Case359
 9.6Tests about a Population Proportion362
   Using Excel to Conduct Hypothesis Tests about a Population Proportion365
  Key Formulas371
  Supplementary Exercises371
 Case Problem 1Unemployment Study373
 Case Problem 2Quality Associates, Inc.373
Chapter 10Comparisons Involving Means375
  Statistics in Practice: Fisons Corporation376
 10.1Estimation of the Difference between the Means of Two Populations: Independent Samples377
   Sampling Distribution of x[subscript 1]--x[subscript 2]379
   Large-Sample Case379
   Using Excel: Large-Sample Case381
   Small-Sample Case382
   Using Excel: Small-Sample Case385
 10.2Hypothesis Tests about the Difference between the Means of Two Populations: Independent Samples390
   Large-Sample Case390
   Using Excel: Large-Sample Case392
   Small-Sample Case394
   Using Excel: Small-Sample Case396
 10.3Inferences about the Difference between the Means of Two Populations: Matched Samples400
   Using Excel402
 10.4Introduction to Analysis of Variance407
   Assumptions for Analysis of Variance409
   Conceptual Overview411
 10.5Analysis of Variance: Testing for the Equality of k Population Means411
   Between-Treatments Estimate of Population Variance413
   Within-Treatments Estimate of Population Variance413
   Comparing the Variance Estimates: The F Test414
   ANOVA Table415
   Using Excel to Test for the Equality of k Population Means416
  Key Formulas422
  Supplementary Exercises424
 Case Problem 1Par, Inc.428
 Case Problem 2Wentworth Medical Center428
 Case Problem 3Compensation for ID Professionals429
Chapter 11Comparisons Involving Proportions431
  Statistics in Practice: United Way432
 11.1Inferences about the Differences between the Proportions of Two Populations433
   Sampling Distribution of p[subscript 1]--p[subscript 2]433
   Interval Estimation of p[subscript 1]--p[subscript 2]434
   Using Excel to Develop an Interval Estimate of p[subscript 1]--p[subscript 2]435
   Hypothesis Tests about p[subscript 1]--p[subscript 2]436
   Using Excel to Conduct a Hypothesis Test about p[subscript 1]--p[subscript 2]438
 11.2Hypothesis Test for Proportions of a Multinomial Population441
   Using Excel to Conduct a Goodness of Fit Test444
 11.3Test of Independence: Contingency Tables448
   Using Excel to Conduct a Test of Independence451
  Key Formulas457
  Supplementary Exercises458
  Case Problem: Bipartisan Agenda for Change461
Chapter 12Regression Analysis463
  Statistics in Practice: Polaroid Corporation464
 12.1Simple Linear Regression Model465
   Regression Model and the Regression Equation465
   Estimated Regression Equation466
 12.2Least Squares Method467
   Using Excel to Develop a Scatter Diagram and Compute the Estimated Regression Equation472
 12.3Coefficient of Determination478
   Using Excel to Compute the Coefficient of Determination482
   Correlation Coefficient482
 12.4Model Assumptions487
 12.5Testing for Significance488
   An Estimate of [sigma superscript 2]489
   t Test489
   Confidence Interval for [beta subscript 1]491
   F Test492
   Some Cautions about the Interpretation of Significance Tests493
 12.6Excel's Regression Tool497
   Using Excel's Regression Tool for the Armand's Pizza Parlors Problem497
   Interpretation of Estimated Regression Equation Output498
   Interpretation of ANOVA Output500
   Interpretation of Regression Statistics Output501
 12.7Using the Estimated Regression Equation for Estimation and Prediction505
   Point Estimation505
   Interval Estimation505
   Confidence Interval Estimate of the Mean Value of y506
   Prediction Interval Estimate of an Individual Value of y508
   Using Excel to Develop Confidence and Prediction Interval Estimates509
 12.8Residual Analysis: Validating Model Assumptions513
   Residual Plot against x514
   Using Excel's Regression Tool to Construct a Residual Plot516
 12.9Multiple Regression519
   An Example: Butler Trucking Company520
   Using Excel's Regression Tool to Develop the Estimated Multiple Regression Equation523
   A Note on Interpretation of Coefficients525
   Testing for Significance526
   Multiple Coefficient of Determination527
   Estimation and Prediction527
  Key Formulas533
  Supplementary Exercises535
 Case Problem 1Spending and Student Achievement541
 Case Problem 2U.S. Department of Transportation543
Chapter 13Statistical Methods for Quality Control544
  Statistics in Practice: Dow Chemical545
 13.1Statistical Process Control546
   Control Charts547
   x Chart: Process Mean and Standard Deviation Known548
   x Chart: Process Mean and Standard Deviation Unknown550
   R Chart553
   Using Excel to Construct an R Chart and an x Chart555
   p Chart558
   np Chart560
   Interpretation of Control Charts561
 13.2Acceptance Sampling564
   KALI, Inc.: An Example of Acceptance Sampling565
   Computing the Probability of Accepting a Lot566
   Selecting an Acceptance Sampling Plan567
   Multiple Sampling Plans570
  Key Formulas573
  Supplementary Exercises574
Appendix AReferences and Bibliography2
Appendix BTables3
Appendix CSummation Notation13
Appendix DAnswers to Even-Numbered Exercises15
Appendix ESolutions to Self-Test Exercises28
Appendix FExcel Functions and the Function Wizard44


Location Call no. Vol. Availability
Description 1 volume (various pagings) : illustrations ; 26 cm + 1 computer optical disc (4 3/4 in.)
Bibliography Includes bibliographical references and index
Subject Microsoft Excel (Computer file)
Commercial statistics.
Commercial statistics -- Computer programs.
Author Sweeney, Dennis J.
Williams, Thomas A. (Thomas Arthur), 1944-
LC no. 00030772
ISBN 032402083X