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Basic Statistics For Business & Economics: Basic Statistics For Business And Economics,9780072984019
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Basic Statistics For Business & Economics: Basic Statistics For Business And Economics

by ; ;
Edition:
5th
ISBN13:

9780072984019

ISBN10:
0072984015
Format:
Hardcover
Pub. Date:
12/1/2004
Publisher(s):
McGraw-Hill

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Summary

The Fifth Edition of Basic Statistics for Business and Economics is a shorter version of Lind/Marchal/Wathen's Statistical Techniques in Business and Economics, 12e. The authors of this text continue to provide a student-oriented approach to business statistics. In this book you will find step-by-step solved examples, realistic exercises, and up-to-date technology and illustrations. Book jacket.

Table of Contents

What Is Statistics?p. 1
Introductionp. 2
Why Study Statistics?p. 2
What Is Meant by Statistics?p. 4
Types of Statisticsp. 6
Descriptive Statisticsp. 6
Inferential Statisticsp. 7
Types of Variablesp. 9
Levels of Measurementp. 9
Nominal-Level Datap. 10
Ordinal-Level Datap. 11
Interval-Level Datap. 12
Ratio-Level Datap. 12
Exercisesp. 14
Statistics, Graphics, and Ethicsp. 15
Misleading Statisticsp. 15
Association Does Not Necessarily Imply Causationp. 15
Graphs Can Be Misleadingp. 16
Become a Better Consumer and a Better Producer of Informationp. 17
Ethicsp. 17
Software Applicationsp. 18
Chapter Outlinep. 19
Chapter Exercisesp. 19
exercises.comp. 20
Dataset Exercisesp. 21
Answers to Self-Reviewp. 22
Describing Data: Frequency Distributions and Graphic Presentationp. 23
Introductionp. 24
Constructing a Frequency Distributionp. 25
Class Intervals and Class Midpointsp. 29
A Software Examplep. 29
Relative Frequency Distributionp. 30
Exercisesp. 31
Graphic Presentation of a Frequency Distributionp. 32
Histogramp. 32
Frequency Polygonp. 34
Exercisesp. 37
Cumulative Frequency Distributionsp. 38
Exercisesp. 41
Other Graphic Presentations of Datap. 42
Line Graphsp. 42
Bar Chartsp. 43
Pie Chartsp. 44
Exercisesp. 46
Chapter Outlinep. 47
Chapter Exercisesp. 48
exercises.comp. 53
Dataset Exercisesp. 53
Software Commandsp. 54
Answers to Self-Reviewp. 56
Describing Data: Numerical Measuresp. 57
Introductionp. 58
The Population Meanp. 59
The Sample Meanp. 60
Properties of the Arithmetic Meanp. 61
Exercisesp. 62
The Weighted Meanp. 63
Exercisesp. 64
The Medianp. 64
The Modep. 65
Exercisesp. 67
Software Solutionp. 68
The Relative Positions of the Mean, Median, and Modep. 68
Exercisesp. 70
The Geometric Meanp. 71
Exercisesp. 72
Why Study Dispersion?p. 73
Measures of Dispersionp. 74
Rangep. 74
Mean Deviationp. 75
Exercisesp. 76
Variance and Standard Deviationp. 77
Exercisesp. 79
Software Solutionp. 80
Exercisesp. 81
Interpretation and Uses of the Standard Deviationp. 82
Chebyshev's Theoremp. 82
The Empirical Rulep. 83
Exercisesp. 84
Chapter Outlinep. 84
Pronunciation Keyp. 86
Chapter Exercisesp. 86
exercises.comp. 89
Dataset Exercisesp. 90
Software Commandsp. 90
Answers to Self-Reviewp. 92
Describing Data: Displaying and Exploring Datap. 93
Introductionp. 94
Dot Plotsp. 94
Exercisesp. 96
Quartiles, Deciles, and Percentilesp. 97
Exercisesp. 100
Box Plotsp. 100
Exercisesp. 102
Skewnessp. 103
Exercisesp. 107
Describing the Relationship between Two Variablesp. 107
Exercisesp. 110
Chapter Outlinep. 112
Pronunciation Keyp. 112
Chapter Exercisesp. 112
exercises.comp. 116
Dataset Exercisesp. 116
Software Commandsp. 117
Answers to Self-Reviewp. 119
A Survey of Probability Conceptsp. 120
Introductionp. 121
What Is a Probability?p. 122
Approaches to Assigning Probabilitiesp. 124
Classical Probabilityp. 124
Empirical Probabilityp. 125
Subjective Probabilityp. 126
Exercisesp. 127
Some Rules for Computing Probabilitiesp. 128
Rules of Additionp. 128
Exercisesp. 133
Rules of Multiplicationp. 134
Contingency Tablesp. 137
Tree Diagramsp. 139
Exercisesp. 141
Principles of Countingp. 142
The Multiplication Formulap. 142
The Permutation Formulap. 143
The Combination Formulap. 145
Exercisesp. 146
Chapter Outlinep. 147
Pronunciation Keyp. 148
Chapter Exercisesp. 148
exercises.comp. 152
Dataset Exercisesp. 152
Software Commandsp. 153
Answers to Self-Reviewp. 154
Discrete Probability Distributionsp. 156
Introductionp. 157
What Is a Probability Distribution?p. 157
Random Variablesp. 159
Discrete Random Variablep. 159
Continuous Random Variablep. 160
The Mean, Variance, and Standard Deviation of a Probability Distributionp. 160
Meanp. 160
Variance and Standard Distributionp. 161
Exercisesp. 163
Binomial Probability Distributionp. 164
How Is a Binomial Probability Distribution Computedp. 165
Binomial Probability Tablesp. 167
Exercisesp. 170
Cumulative Binomial Probability Distributionsp. 172
Exercisesp. 173
Poisson Probability Distributionp. 174
Exercisesp. 177
Chapter Outlinep. 177
Chapter Exercisesp. 178
Dataset Exercisesp. 182
Software Commandsp. 182
Answers to Self-Reviewp. 184
Continuous Probability Distributionsp. 185
Introductionp. 186
The Family of Uniform Distributionsp. 186
Exercisesp. 189
The Family of Normal Probability Distributionsp. 190
The Standard Normal Distributionp. 193
The Empirical Rulep. 195
Exercisesp. 196
Finding Areas under the Normal Curvep. 197
Exercisesp. 199
Exercisesp. 202
Exercisesp. 204
Chapter Outlinep. 204
Chapter Exercisesp. 205
Dataset Exercisesp. 208
Software Commandsp. 209
Answers to Self-Reviewp. 210
Sampling Methods and the Central Limit Theoremp. 211
Introductionp. 212
Sampling Methodsp. 212
Reasons to Samplep. 212
Simple Random Samplingp. 213
Systematic Random Samplingp. 216
Stratified Random Samplingp. 216
Cluster Samplingp. 217
Exercisesp. 218
Sampling "Error"p. 220
Sampling Distribution of the Sample Meanp. 222
Exercisesp. 225
The Central Limit Theoremp. 226
Exercisesp. 232
Using the Sampling Distribution of the Sample Meanp. 233
Exercisesp. 237
Chapter Outlinep. 237
Pronunciation Keyp. 238
Chapter Exercisesp. 238
exercises.comp. 242
Dataset Exercisesp. 243
Software Commandsp. 243
Answers to Self-Reviewp. 244
Estimation and Confidence Intervalsp. 245
Introductionp. 246
Point Estimates and Confidence Intervalsp. 246
Known [sigma] or a Large Samplep. 246
A Computer Simulationp. 251
Exercisesp. 253
Unknown Population Standard Deviation and a Small Samplep. 254
Exercisesp. 260
A Confidence Interval for a Proportionp. 260
Exercisesp. 263
Finite-Population Correction Factorp. 263
Exercisesp. 264
Choosing an Appropriate Sample Sizep. 265
Exercisesp. 267
Chapter Outlinep. 268
Pronunciation Keyp. 269
Chapter Exercisesp. 269
exercises.comp. 272
Dataset Exercisesp. 273
Software Commandsp. 273
Answers to Self-Reviewp. 275
One-Sample Tests of Hypothesisp. 276
Introductionp. 277
What Is a Hypothesis?p. 277
What Is Hypothesis Testing?p. 278
Five-Step Procedure for Testing a Hypothesisp. 278
State the Null Hypothesis (H[subscript 0]) and the Alternate Hypothesis (H[subscript 1])p. 278
Select a Level of Significancep. 279
Select the Test Statisticp. 279
Formulate the Decision Rulep. 281
Make a Decisionp. 282
One-Tailed and Two-Tailed Tests of Significancep. 283
Testing for a Population Mean with a Known Population Standard Deviationp. 284
A Two-Tailed Testp. 284
A One-Tailed Testp. 288
p-Value in Hypothesis Testingp. 288
Testing for a Population Mean: Large Sample, Population Standard Deviation Unknownp. 290
Exercisesp. 291
Tests Concerning Proportionsp. 292
Exercisesp. 295
Testing for a Population Mean: Small Sample, Population Standard Deviation Unknownp. 295
Exercisesp. 300
A Software Solutionp. 301
Exercisesp. 303
Chapter Outlinep. 304
Pronunciation Keyp. 305
Chapter Exercisesp. 305
exercises.comp. 309
Dataset Exercisesp. 309
Software Commandsp. 310
Answers to Self-Reviewp. 311
Two-Sample Tests of Hypothesisp. 312
Introductionp. 313
Two-Sample Tests of Hypothesis: Independent Samplesp. 313
Exercisesp. 318
Two-Sample Tests about Proportionsp. 319
Exercisesp. 321
Comparing Population Means with Small Samplesp. 323
Exercisesp. 326
Two-Sample Tests of Hypothesis: Dependent Samplesp. 327
Comparing Dependent and Independent Samplesp. 331
Exercisesp. 333
Chapter Outlinep. 334
Pronunciation Keyp. 335
Chapter Exercisesp. 335
exercises.comp. 340
Dataset Exercisesp. 341
Software Commandsp. 341
Answers to Self-Reviewp. 342
Analysis of Variancep. 344
Introductionp. 345
The F Distributionp. 345
Comparing Two Population Variancesp. 346
Exercisesp. 349
ANOVA Assumptionsp. 350
The ANOVA Testp. 352
Exercisesp. 359
Inferences about Pairs of Treatment Meansp. 360
Exercisesp. 362
Chapter Outlinep. 364
Pronunciation Keyp. 365
Chapter Exercisesp. 365
exercises.comp. 370
Dataset Exercisesp. 370
Software Commandsp. 371
Answers to Self-Reviewp. 373
Linear Regression and Correlationp. 374
Introductionp. 375
What Is Correlation Analysis?p. 375
The Coefficient of Correlationp. 377
The Coefficient of Determinationp. 381
Correlation and Causep. 382
Exercisesp. 382
Testing the Significance of the Correlation Coefficientp. 384
Exercisesp. 386
Regression Analysisp. 386
Least Squares Principlep. 386
Drawing the Line of Regressionp. 389
Exercisesp. 390
The Standard Error of Estimatep. 392
Assumptions Underlying Linear Regressionp. 395
Exercisesp. 396
Confidence and Prediction Intervalsp. 396
Exercisesp. 400
More on the Coefficient of Determinationp. 400
Exercisesp. 403
The Relationships among the Coefficient of Correlation, the Coefficient of Determination, and the Standard Error of Estimatep. 403
Transforming Datap. 405
Exercisesp. 407
Chapter Outlinep. 408
Pronunciation Keyp. 410
Chapter Exercisesp. 410
exercises.comp. 417
Dataset Exercisesp. 417
Software Commandsp. 418
Answers to Self-Reviewp. 420
Multiple Regression and Correlation Analysisp. 421
Introductionp. 422
Multiple Regression Analysisp. 422
Inferences in Multiple Linear Regressionp. 423
Exercisesp. 426
Multiple Standard Error of Estimatep. 428
Assumptions about Multiple Regression and Correlationp. 429
The ANOVA Tablep. 430
Exercisesp. 432
Evaluating the Regression Equationp. 432
Using a Scatter Diagramp. 432
Correlation Matrixp. 433
Global Test: Testing the Multiple Regression Modelp. 434
Evaluating Individual Regression Coefficientsp. 436
Qualitative Independent Variablesp. 439
Exercisesp. 441
Analysis of Residualsp. 442
Chapter Outlinep. 447
Pronunciation Keyp. 448
Chapter Exercisesp. 448
exercises.comp. 459
Dataset Exercisesp. 460
Software Commandsp. 461
Answers to Self-Reviewp. 463
Chi-Square Applicationsp. 464
Introductionp. 464
Goodness-of-Fit Test: Equal Expected Frequenciesp. 465
Exercisesp. 470
Goodness-of-Fit Test: Unequal Expected Frequenciesp. 471
Limitations of Chi-Squarep. 473
Exercisesp. 475
Contingency Table Analysisp. 746
Exercisesp. 450
Chapter Outlinep. 481
Pronunciation Keyp. 481
Chapter Exercisesp. 482
exercises.comp. 484
Dataset Exercisesp. 485
Software Commandsp. 486
Answers to Self-Reviewp. 487
CD Chapters
Statistical Quality Control
Time Series and Forecasting
Appendixes
Tables
Binomial Probability Distributionp. 489
Critical Values of Chi-Squarep. 494
Poisson Distributionp. 495
Areas under the Normal Curvep. 496
Table of Random Numbersp. 497
Student's t Distributionp. 498
Critical Values of the F Distributionp. 499
Wilcoxon T Valuesp. 501
Factors for Control Chartsp. 502
Datasets
Real Estatep. 503
Major League Baseballp. 506
Wages and Wage Earnersp. 508
CIA International Economic and Demographic Datap. 512
Whitner Autoplexp. 515
Getting Started with Megastatp. 516
Visual Statisticsp. 520
Answers to Odd-Numbered Exercisesp. 525
Photo Creditsp. 552
Indexp. 553
Table of Contents provided by Ingram. All Rights Reserved.


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