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Gerald Keller's new APPLIED STATISTICS WITH MICROSOFT- EXCEL integrates Excel into the general introductory statistics course. Keller, the co-author of the market-leading STATISTICS FOR MANAGEMENT AND ECONOMICS, Fifth Edition, incorporates his proven three-step problem-solving process throughout this book. The first step, Identify, is the work a statistician does before the calculations are performed, which entails organizing the experiment, gathering the data, and deciding which statistical techniques to employ. The second step, Compute, is the computation with Excel. In this step, Keller shows the manual calculation for the simplest of techniques only. For example, he describes how to calculate the sample mean, variance, and standard deviation, how to compute the z-interval estimate of, and the z-test of. The third step, Interpret, is the interpretation of the computer output, which requires an understanding of statistical concepts."

Tabla de contenidos provista por Syndetics

• 1 What is Statistics?(p. 1)
• 1.1 Introduction(p. 2)
• 1.2 Key Statistical Concepts(p. 6)
• 1.3 Statistics and the Computer(p. 7)
• 1.4 World Wide Web and Learning Center(p. 7)
• Appendix 1.A Introduction to Microsoft Excel(p. 10)
• 2 Graphical Descriptive Techniques(p. 15)
• 2.1 Introduction(p. 16)
• 2.2 Types of Data(p. 16)
• 2.3 Graphically Describing Interval Data: Frequency Distributions and Histograms(p. 20)
• 2.4 Graphically Describing Nominal Data: Bar and Pie Charts(p. 33)
• 2.5 Describing Time-Series Data: Line Charts(p. 38)
• 2.6 Describing the Relationship between Two Interval Variables: Scatter Diagrams(p. 42)
• 2.7 Summary(p. 49)
• 3 Numerical Descriptive Techniques for Interval Data(p. 52)
• 3.1 Introduction(p. 53)
• 3.2 Measures of Central Location(p. 54)
• 3.3 Measures of Variability(p. 60)
• 3.4 Other Measures of Shape (Optional)(p. 70)
• 3.5 Measures of Relative Standing and Box Plots(p. 71)
• 3.6 Measures of Linear Relationship(p. 76)
• 3.7 General Guidelines for Exploring Data(p. 84)
• 3.8 Summary(p. 85)
• 4 Probability(p. 89)
• 4.1 Introduction(p. 90)
• 4.2 Assigning Probability to Events(p. 90)
• 4.3 Joint, Marginal, and Conditional Probability(p. 95)
• 4.4 Probability Rules and Trees(p. 103)
• 4.5 Summary(p. 113)
• Case 4.1 Let's Make a Deal(p. 116)
• Case 4.2 To Bunt or Not to Bunt, That Is the Question(p. 116)
• 5 Random Variables and Discrete Probability Distributions(p. 118)
• 5.1 Introduction(p. 119)
• 5.2 Random Variables and Probability Distributions(p. 119)
• 5.3 Describing the Population/Probability Distribution(p. 124)
• 5.4 Binomial Distribution(p. 128)
• 5.5 Poisson Distribution(p. 136)
• 5.6 Summary(p. 141)
• Case 5.1 To Bunt or Not to Bunt, That Is the Question, Part II(p. 145)
• 6 Continuous Probability Distributions(p. 146)
• 6.1 Introduction(p. 147)
• 6.2 Probability Density Functions(p. 147)
• 6.3 Normal Distribution(p. 153)
• 6.4 Other Continuous Distributions(p. 170)
• 6.5 Summary(p. 187)
• 7 Sampling and Sampling Plans(p. 188)
• 7.1 Introduction(p. 189)
• 7.2 Sampling(p. 189)
• 7.3 Sampling Plans(p. 191)
• 7.4 Errors Involved in Sampling(p. 196)
• 7.5 Summary(p. 198)
• 8 Sampling Distributions(p. 199)
• 8.1 Introduction(p. 200)
• 8.2 Sampling Distribution of the Mean(p. 200)
• 8.3 Creating the Sampling Distribution by Computer Simulation (Optional)(p. 212)
• 8.4 Sampling Distribution of a Proportion(p. 215)
• 8.5 Sampling Distribution of the Difference between Two Means(p. 220)
• 8.6 From Here to Inference(p. 223)
• 8.7 Summary(p. 224)
• 9 Introduction to Estimation(p. 227)
• 9.1 Introduction(p. 228)
• 9.2 Concepts of Estimation(p. 228)
• 9.3 Estimating the Population Mean when the Population Standard Deviation Is Known(p. 232)
• 9.4 Selecting the Sample Size(p. 245)
• 9.5 Simulation Experiments (Optional)(p. 247)
• 9.6 Summary(p. 250)
• 10 Introduction to Hypothesis Testing(p. 253)
• 10.1 Introduction(p. 254)
• 10.2 Concepts of Hypothesis Testing(p. 255)
• 10.3 Testing the Population Mean when the Population Standard Deviation Is Known(p. 257)
• 10.4 Calculating the Probability of a Type II Error(p. 279)
• 10.5 The Road Ahead(p. 288)
• 10.6 Summary(p. 291)
• 11 Inference About A Single Population(p. 293)
• 11.1 Introduction(p. 294)
• 11.2 Inference about a Population Mean when the Standard Deviation Is Unknown(p. 295)
• 11.3 Inference about a Population Variance(p. 305)
• 11.4 Inference about a Population Proportion(p. 311)
• 11.5 Summary(p. 323)
• Case 11.1 Pepsi's Exclusivity Agreement with a University(p. 327)
• Case 11.2 Pepsi's Exclusivity Agreement with a University: The Coke Side of the Equation(p. 328)
• Case 11.3 Number of Uninsured Motorists(p. 328)
• 12 Inference About Two Populations(p. 330)
• 12.1 Introduction(p. 331)
• 12.2 Inference about the Difference between Two Means: Independent Samples(p. 332)
• 12.3 Observational and Experimental Data(p. 348)
• 12.4 Inference about the Difference between Two Means: Matched Pairs Experiment(p. 349)
• 12.5 Inference about the Ratio of Two Variances(p. 361)
• 12.6 Inference about the Difference between Two Population Proportions(p. 367)
• 12.7 Summary(p. 378)
• Case 12.1 Bonanza International(p. 386)
• Case 12.2 Accounting Course Exemptions(p. 387)
• 13 Statistical Inference: Review of Chapters 11 and 12(p. 388)
• 13.1 Introduction(p. 389)
• 13.2 Guide to Identifying the Correct Technique: Chapters 11 and 12(p. 389)
• Case 13.1 Quebec Separation: Oui ou non?(p. 403)
• Case 13.2 Host Selling and Announcer Commercials(p. 403)
• 14 Analysis of Variance(p. 405)
• 14.1 Introduction(p. 406)
• 14.2 Single-Factor (One-Way) Analysis of Variance: Independent Samples(p. 407)
• 14.3 Analysis of Variance Experimental Designs(p. 423)
• 14.4 Single-Factor Analysis of Variance: Randomized Blocks(p. 425)
• 14.5 Two-Factor Analysis of Variance: Independent Samples(p. 434)
• 14.6 Multiple Comparisons(p. 449)
• 14.7 Bartlett's Test(p. 455)
• 14.8 Summary(p. 457)
• 15 Chi-Squared Tests(p. 464)
• 15.1 Introduction(p. 465)
• 15.2 Chi-Squared Goodness-of-Fit Test(p. 465)
• 15.3 Chi-Squared Test of a Contingency Table(p. 472)
• 15.4 Summary of Tests on Nominal Data(p. 482)
• 15.5 Chi-Squared Test for Normality(p. 484)
• 15.6 Summary(p. 489)
• Case 15.1 Predicting the Outcomes of Basketball, Baseball, Football, and Hockey Games from Intermediate Results(p. 493)
• Case 15.2 Can Exposure to a Code of Professional Ethics Help Make Managers More Ethical?(p. 494)
• 16 Nonparametric Statistical Techniques(p. 496)
• 16.1 Introduction(p. 497)
• 16.2 Wilcoxon Rank Sum Test(p. 499)
• 16.3 Sign Test and Wilcoxon Signed Rank Sum Test(p. 511)
• 16.4 Kruskal-Wallis Test(p. 524)
• 16.5 Friedman Test(p. 529)
• 16.6 Summary(p. 535)
• 17 Simple Linear Regression and Correlation(p. 542)
• 17.1 Introduction(p. 543)
• 17.2 Model(p. 544)
• 17.3 Estimating the Coefficients(p. 546)
• 17.4 Error Variable: Required Conditions(p. 552)
• 17.5 Assessing the Model(p. 555)
• 17.6 Using the Regression Equation(p. 564)
• 17.7 Coefficients of Correlation(p. 568)
• 17.8 Regression Diagnostics I(p. 574)
• 17.9 Summary(p. 580)
• Case 17.1 Predicting University Grades from High School Grades(p. 585)
• Case 17.2 Insurance Compensation for Lost Revenues(p. 586)
• 18 Multiple Regression(p. 588)
• 18.1 Introduction(p. 589)
• 18.2 Model and Required Conditions(p. 589)
• 18.3 Estimating the Coefficients and Assessing the Model(p. 590)
• 18.4 Regression Diagnostics II(p. 605)
• 18.5 Regression Diagnostics III (Time Series)(p. 612)
• 18.6 Nominal Independent Variables(p. 623)
• 18.7 Summary(p. 630)
• Case 18.1 Quebec Referendum Vote: Was There Electoral Fraud?(p. 634)
• Case 18.2 Quebec Referendum Vote: The Rebuttal(p. 635)
• 19 Statistical Inference: Conclusion(p. 636)
• 19.1 Introduction(p. 637)
• 19.2 Identifying the Correct Technique: Summary of Statistical Inference(p. 637)
• Case 19.1 Do Banks Discriminate against Women Business Owners? I(p. 644)
• Case 19.2 Do Banks Discriminate against Women Business Owners? II(p. 647)
• 19.3 The Last Word(p. 653)
• Case 19.3 Ambulance and Fire Department Response Interval Study(p. 665)
• Case 19.4 PC Magazine Survey(p. 666)
• Case 19.5 WLU Graduate Survey(p. 667)
• Case 19.6 Evaluation of a New Antidepressant Drug(p. 668)
• Case 19.7 Nutrition Education Programs(p. 669)
• Case 19.8 Do Banks Discriminate against Women Business Owners? III(p. 670)
• Appendix A Sample Statistics from Data Files in Chapters 9 and 10(p. 1)
• Appendix B Tables(p. 1)
• Appendix C Answers to Selected Even-Numbered Exercises(p. 1)
• Index(p. 1)