Title Contemporary business statistics with Microsoft Excel / David R. Anderson, Dennis J. Sweeney, Thomas A. Williams

Published Cincinnati, Ohio : South-Western College Pub., [2001] ©2001

Table of Contents
	Preface					xv
	About the Authors					xx
Chapter 1	Data and Statistics					1
		Statistics in Practice: Business Week				2
	1.1	Applications in Business and Economics				3
			Accounting			3
			Finance			4
			Marketing			4
			Production			4
			Economics			4
	1.2	Data				5
			Elements, Variables, and Observations			5
			Qualitative and Quantitative Data			6
			Cross-Sectional and Time Series Data			7
	1.3	Data Sources				7
			Existing Sources			7
			Statistical Studies			10
			Data Acquisition Errors			11
	1.4	Descriptive Statistics				12
	1.5	Statistical Inference				14
	1.6	Statistical Analysis Using Microsoft Excel				15
			Data Sets and Excel Worksheets			16
			Using Excel for Statistical Analysis			17
		Summary				18
		Glossary				19
		Exercises				20
Chapter 2	Descriptive Statistics: Tabular and Graphical Methods					25
		Statistics in Practice: Colgate-Palmolive Company				26
	2.1	Summarizing Qualitative Data				27
			Frequency Distribution			27
			Using Excel's COUNTIF Function to Construct a Frequency Distribution			28
			Relative Frequency and Percent Frequency Distributions			28
			Using Excel to Construct Relative Frequency and Percent Frequency Distributions			30
			Bar Graphs and Pie Charts			30
			Using Excel's Chart Wizard to Construct Bar Graphs and Pie Charts			32
			Exercises			34
	2.2	Summarizing Quantitative Data				37
			Frequency Distribution			37
			Using Excel's FREQUENCY Function to Construct a Frequency Distribution			38
			Relative Frequency and Percent Frequency Distributions			40
			Histogram			40
			Using Excel's Chart Wizard to Construct a Histogram			41
			Cumulative Distributions			42
			Ogive			44
			Exercises			46
	2.3	Exploratory Data Analysis: The Stem-and-Leaf Display				49
			Exercises			52
	2.4	Crosstabulations and Scatter Diagrams				54
			Crosstabulation			54
			Using Excel's PivotTable Report to Construct a Crosstabulation			56
			Scatter Diagram			60
			Using Excel's Chart Wizard to Construct a Scatter Diagram			61
			Exercises			64
		Summary				66
		Glossary				67
		Key Formulas				67
		Supplementary Exercises				68
		Case Problem: Consolidated Foods				73
	Appendix 2.1	Using Excel's Histogram Tool to Construct a Frequency Distribution and Histogram				74
Chapter 3	Descriptive Statistics: Numerical Methods					78
		Statistics in Practice: Small Fry Design				79
	3.1	Measures of Location				80
			Mean			80
			Median			81
			Mode			82
			Using Excel to Compute the Mean, Median, and Mode			83
			Percentiles			84
			Quartiles			85
			Sorting Data and Using Excel to Compute Percentiles and Quartiles			87
			Exercises			88
	3.2	Measures of Variability				91
			Range			92
			Interquartile Range			92
			Variance			93
			Standard Deviation			94
			Using Excel to Compute the Sample Variance and Sample Standard Deviation			95
			Coefficient of Variation			96
			Using Excel's Descriptive Statistics Tool			97
			Exercises			99
	3.3	Measures of Relative Location and Detecting Outliers				101
			z-Scores			101
			Chebyshev's Theorem			102
			Empirical Rule			103
			Detecting Outliers			104
			Exercises			104
	3.4	Exploratory Data Analysis				106
			Five-Number Summary			106
			Box Plot			107
			Exercises			108
	3.5	Measures of Association between Two Variables				110
			Covariance			111
			Interpretation of the Covariance			113
			Correlation Coefficient			115
			Interpretation of the Correlation Coefficient			116
			Using Excel to Compute the Covariance and Correlation Coefficient			117
			Exercises			118
	3.6	The Weighted Mean and Working with Grouped Data				120
			Weighted Mean			121
			Grouped Data			122
			Exercises			124
		Summary				126
		Glossary				127
		Key Formulas				128
		Supplementary Exercises				129
	Case Problem 1	Consolidated Foods, Inc.				132
	Case Problem 2	National Health Care Association				133
	Case Problem 3	Business Schools of Asia-Pacific				134
Chapter 4	Introduction to Probability					137
		Statistics in Practice: Morton International				138
	4.1	Experiments, Counting Rules, and Assigning Probabilities				139
			Counting Rules, Combinations, and Permutations			140
			Assigning Probabilities			144
			Probabilities for the KP&L Project			146
			Exercises			148
	4.2	Events and Their Probabilities				149
			Exercises			151
	4.3	Some Basic Relationships of Probability				153
			Complement of an Event			153
			Addition Law			154
			Exercises			157
	4.4	Conditional Probability				158
			Independent Events			162
			Multiplication Law			162
			Exercises			164
	4.5	Bayes' Theorem				166
			Tabular Approach			170
			Using Excel to Compute Posterior Probabilities			170
			Exercises			171
		Summary				173
		Glossary				173
		Key Formulas				174
		Supplementary Exercises				175
		Case Problem: Hamilton County Judges				179
Chapter 5	Discrete Probability Distributions					181
		Statistics in Practice: Citibank				182
	5.1	Random Variables				183
			Discrete Random Variables			183
			Continuous Random Variables			183
			Exercises			185
	5.2	Discrete Probability Distributions				186
			Exercises			188
	5.3	Expected Value and Variance				191
			Expected Value			191
			Variance			191
			Using Excel to Compute the Expected Value, Variance, and Standard Deviation			192
			Exercises			193
	5.4	Binomial Probability Distribution				196
			A Binomial Experiment			197
			Martin Clothing Store Problem			198
			Using Excel to Compute Binomial Probabilities			202
			Expected Value and Variance for the Binomial Probability Distribution			204
			Exercises			205
	5.5	Poisson Probability Distribution				207
			An Example Involving Time Intervals			208
			An Example Involving Length or Distance Intervals			208
			Using Excel to Compute Poisson Probabilities			209
			Exercises			211
	5.6	Hypergeometric Probability Distribution				212
			Using Excel to Compute Hypergeometric Probabilities			214
			Exercises			214
		Summary				215
		Glossary				216
		Key Formulas				216
		Supplementary Exercises				217
Chapter 6	Continuous Probability Distributions					220
		Statistics in Practice: Procter & Gamble				221
	6.1	Uniform Probability Distribution				222
			Area as a Measure of Probability			223
			Exercises			225
	6.2	Normal Probability Distribution				226
			Normal Curve			227
			Standard Normal Probability Distribution			229
			Computing Probabilities for Any Normal Probability Distribution			234
			Grear Tire Company Problem			235
			Using Excel to Compute Normal Probabilities			237
			Exercises			240
	6.3	Exponential Probability Distribution				242
			Computing Probabilities for the Exponential Distribution			243
			Relationship between the Poisson and Exponential Distributions			244
			Using Excel to Compute the Exponential Probabilities			245
			Exercises			246
		Summary				247
		Glossary				247
		Key Formulas				248
		Supplementary Exercises				248
Chapter 7	Sampling and Sampling Distributions					251
		Statistics in Practice: Mead Corporation				252
	7.1	The Electronics Associates Sampling Problem				253
	7.2	Simple Random Sampling				254
			Sampling from Finite Populations			254
			Using Excel to Select a Simple Random Sample			256
			Sampling from Infinite Populations			258
			Exercises			259
	7.3	Point Estimation				261
			Exercises			263
	7.4	Introduction to Sampling Distributions				264
	7.5	Sampling Distribution of x				267
			Expected Value of x			268
			Standard Deviation of x			268
			Central Limit Theorem			270
			Sampling Distribution of x for the EAI Problem			272
			Practical Value of the Sampling Distribution of x			272
			Relationship between the Sample Size and the Sampling Distribution of x			274
			Exercises			276
	7.6	Sampling Distribution of p				278
			Expected Value of p			278
			Standard Deviation of p			278
			Form of the Sampling Distribution of p			279
			Practical Value of the Sampling Distribution of p			280
			Exercises			281
	7.7	Other Sampling Methods				283
			Stratified Random Sampling			283
			Cluster Sampling			284
			Systematic Sampling			284
			Convenience Sampling			285
			Judgment Sampling			285
		Summary				286
		Glossary				286
		Key Formulas				287
		Supplementary Exercises				288
Chapter 8	Interval Estimation					290
		Statistics in Practice: Dollar General Corporation				291
	8.1	Interval Estimation of a Population Mean: Large-Sample Case				292
			CJW Problem			292
			Sampling Error			293
			Constructing an Interval Estimate			294
			Interpreting an Interval Estimate			294
			The General Procedure			296
			Constructing an Interval Estimate: Large-Sample Case with [sigma] Unknown			297
			Using Excel to Construct a Confidence Interval: [sigma] Unknown			298
			Exercises			300
	8.2	Interval Estimation of a Population Mean: Small-Sample Case				301
			Using Excel to Construct a Confidence Interval: [sigma] Unknown			305
			Exercises			308
	8.3	Determining the Sample Size				309
			Exercises			311
	8.4	Interval Estimation of a Population Proportion				312
			Using Excel to Construct a Confidence Interval			313
			Determining the Sample Size			314
			Exercises			316
		Summary				318
		Glossary				319
		Key Formulas				320
		Supplementary Exercises				320
	Case Problem 1	Bock Investment Services				323
	Case Problem 2	Metropolitan Research, Inc.				323
Chapter 9	Hypothesis Testing					326
		Statistics in Practice: Harris Corporation				327
	9.1	Developing Null and Alternative Hypotheses				328
			Testing Research Hypotheses			328
			Testing the Validity of a Claim			328
			Testing in Decision-Making Situations			329
			Summary of Forms for Null and Alternative Hypotheses			329
			Exercises			330
	9.2	Type I and Type II Errors				330
			Exercises			332
	9.3	One-Tailed Tests about a Population Mean: Large-Sample Case				333
			Use of p-Values			337
			Steps of Hypothesis Testing			338
			One-Tailed Tests: Large-Sample Case with [sigma] Unknown			338
			Using Excel to Conduct a One-Tailed Hypothesis Test			340
			Summary: One-Tailed Test about a Population Mean			342
			Exercises			343
	9.4	Two-Tailed Tests about a Population Mean: Large-Sample Case				345
			p-Values for Two-Tailed Tests			347
			Using Excel to Conduct a Two-Tailed Hypothesis Test			348
			Summary: Two-Tailed Tests about a Population Mean			349
			Relationship between Interval Estimation and Hypothesis Testing			350
			Exercises			352
	9.5	Tests about a Population Mean: Small-Sample Case				354
			p-Values and the t Distribution			355
			Using Excel to Conduct a One-Tailed Hypothesis Test: Small-Sample Case			356
			A Two-Tailed Test			358
			Using Excel to Conduct a Two-Tailed Hypothesis Test: Small-Sample Case			359
			Exercises			360
	9.6	Tests about a Population Proportion				362
			Using Excel to Conduct Hypothesis Tests about a Population Proportion			365
			Exercises			367
		Summary				369
		Glossary				371
		Key Formulas				371
		Supplementary Exercises				371
	Case Problem 1	Unemployment Study				373
	Case Problem 2	Quality Associates, Inc.				373
Chapter 10	Comparisons Involving Means					375
		Statistics in Practice: Fisons Corporation				376
	10.1	Estimation of the Difference between the Means of Two Populations: Independent Samples				377
			Sampling Distribution of x[subscript 1]--x[subscript 2]			379
			Large-Sample Case			379
			Using Excel: Large-Sample Case			381
			Small-Sample Case			382
			Using Excel: Small-Sample Case			385
			Exercises			387
	10.2	Hypothesis Tests about the Difference between the Means of Two Populations: Independent Samples				390
			Large-Sample Case			390
			Using Excel: Large-Sample Case			392
			Small-Sample Case			394
			Using Excel: Small-Sample Case			396
			Exercises			398
	10.3	Inferences about the Difference between the Means of Two Populations: Matched Samples				400
			Using Excel			402
			Exercises			404
	10.4	Introduction to Analysis of Variance				407
			Assumptions for Analysis of Variance			409
			Conceptual Overview			411
	10.5	Analysis of Variance: Testing for the Equality of k Population Means				411
			Between-Treatments Estimate of Population Variance			413
			Within-Treatments Estimate of Population Variance			413
			Comparing the Variance Estimates: The F Test			414
			ANOVA Table			415
			Using Excel to Test for the Equality of k Population Means			416
			Exercises			419
		Summary				421
		Glossary				422
		Key Formulas				422
		Supplementary Exercises				424
	Case Problem 1	Par, Inc.				428
	Case Problem 2	Wentworth Medical Center				428
	Case Problem 3	Compensation for ID Professionals				429
Chapter 11	Comparisons Involving Proportions					431
		Statistics in Practice: United Way				432
	11.1	Inferences about the Differences between the Proportions of Two Populations				433
			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
			Exercises			439
	11.2	Hypothesis Test for Proportions of a Multinomial Population				441
			Using Excel to Conduct a Goodness of Fit Test			444
			Exercises			446
	11.3	Test of Independence: Contingency Tables				448
			Using Excel to Conduct a Test of Independence			451
			Exercises			453
		Summary				456
		Glossary				457
		Key Formulas				457
		Supplementary Exercises				458
		Case Problem: Bipartisan Agenda for Change				461
Chapter 12	Regression Analysis					463
		Statistics in Practice: Polaroid Corporation				464
	12.1	Simple Linear Regression Model				465
			Regression Model and the Regression Equation			465
			Estimated Regression Equation			466
	12.2	Least Squares Method				467
			Using Excel to Develop a Scatter Diagram and Compute the Estimated Regression Equation			472
			Exercises			474
	12.3	Coefficient of Determination				478
			Using Excel to Compute the Coefficient of Determination			482
			Correlation Coefficient			482
			Exercises			484
	12.4	Model Assumptions				487
	12.5	Testing for Significance				488
			An Estimate of [sigma superscript 2]			489
			t Test			489
			Confidence Interval for [beta subscript 1]			491
			F Test			492
			Some Cautions about the Interpretation of Significance Tests			493
			Exercises			495
	12.6	Excel's Regression Tool				497
			Using Excel's Regression Tool for the Armand's Pizza Parlors Problem			497
			Interpretation of Estimated Regression Equation Output			498
			Interpretation of ANOVA Output			500
			Interpretation of Regression Statistics Output			501
			Exercises			501
	12.7	Using the Estimated Regression Equation for Estimation and Prediction				505
			Point Estimation			505
			Interval Estimation			505
			Confidence Interval Estimate of the Mean Value of y			506
			Prediction Interval Estimate of an Individual Value of y			508
			Using Excel to Develop Confidence and Prediction Interval Estimates			509
			Exercises			512
	12.8	Residual Analysis: Validating Model Assumptions				513
			Residual Plot against x			514
			Using Excel's Regression Tool to Construct a Residual Plot			516
			Exercises			518
	12.9	Multiple Regression				519
			An Example: Butler Trucking Company			520
			Using Excel's Regression Tool to Develop the Estimated Multiple Regression Equation			523
			A Note on Interpretation of Coefficients			525
			Testing for Significance			526
			Multiple Coefficient of Determination			527
			Estimation and Prediction			527
			Exercises			528
		Summary				531
		Glossary				532
		Key Formulas				533
		Supplementary Exercises				535
	Case Problem 1	Spending and Student Achievement				541
	Case Problem 2	U.S. Department of Transportation				543
Chapter 13	Statistical Methods for Quality Control					544
		Statistics in Practice: Dow Chemical				545
	13.1	Statistical Process Control				546
			Control Charts			547
			x Chart: Process Mean and Standard Deviation Known			548
			x Chart: Process Mean and Standard Deviation Unknown			550
			R Chart			553
			Using Excel to Construct an R Chart and an x Chart			555
			p Chart			558
			np Chart			560
			Interpretation of Control Charts			561
			Exercises			562
	13.2	Acceptance Sampling				564
			KALI, Inc.: An Example of Acceptance Sampling			565
			Computing the Probability of Accepting a Lot			566
			Selecting an Acceptance Sampling Plan			567
			Multiple Sampling Plans			570
			Exercises			571
		Summary				572
		Glossary				572
		Key Formulas				573
		Supplementary Exercises				574
Appendix A	References and Bibliography					2
Appendix B	Tables					3
Appendix C	Summation Notation					13
Appendix D	Answers to Even-Numbered Exercises					15
Appendix E	Solutions to Self-Test Exercises					28
Appendix F	Excel Functions and the Function Wizard					44
	Index					1

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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) http://id.loc.gov/authorities/names/n86025775 Subject Commercial statistics. Commercial statistics -- Computer programs. Author Sweeney, Dennis J. Williams, Thomas A. (Thomas Arthur), 1944- LC no. 00030772 ISBN 032402083X

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