Data Analysis with Microsoft Excel: Updated for Office 2007 / Edition 3

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0495391786 BRAND NEW W/FAST SHIPPING! This item is: Data Analysis with Microsoft? Excel?Updated for Office 2007 (Book Only), 3rd Ed., by Kenneth N. Berk Patrick M. Carey; FORMAT: ... Bound Book; ISBN: 9780495391784. Choose Expedited for fastest shipping! Our 98%+ rating proves our commitment! We cannot ship to PO Boxes/APO Addresses or outside the continental U.S. To avoid ordering the wrong item, please check your item's ISBN number! Read more Show Less

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Reap the benefits of Microsoft® Excel for statistical analysis of real-world data with this best-selling, hands-on text. Data Analysis with Microsoft Excel: Updated for Office 2007® continues to be the text students should own for manipulating spreadsheets in their introductory statistics courses. To reflect the changes in Excel 2007, this edition has been completely updated with new program instructions, screenshots, and command references.

The text includes powerful Excel resources available on its student companion website. The StatPlus add-in vastly expands Excel 2007's statistical capabilities to include advanced graphics such as box plots, control charts, scatter plots, and correlation matrices. Interactive Concept Tutorials provide hands-on visual guides within Excel for learning statistical concepts. Downloadable data sets cover all of the applications in the text and allow students to actively model and explore real data.

Even computer spreadsheet novices will find this text makes solving statistical problems simple. Kenneth N. Berk and Patrick Carey's step-by-step visual approach, numerous examples, handy tips, and intuitive tutorials make it easy and fun to learn how to use statistical methods to analyze data. With the aid of StatPlus, you will be solving real problems and generating professional-looking reports in no time.

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Product Details

  • ISBN-13: 9780495391784
  • Publisher: Cengage Learning
  • Publication date: 6/19/2009
  • Edition description: New Edition
  • Edition number: 3
  • Pages: 596
  • Product dimensions: 7.40 (w) x 9.20 (h) x 1.00 (d)

Meet the Author

Ken Berk has a BS in Physics from Carnegie Tech (now Carnegie Mellon) and a PhD in Mathematics from Minnesota. He is Professor Emeritus of Mathematics at Illinois State University and a Fellow of the American Statistical Association. He founded the Software Reviews section of The American Statistician and edited it for six years. He served as Secretary/Treasurer, Program Chair, and Chair of the Statistical Computing Section of the American Statistical Association, and he twice co-chaired the Interface Symposium, the main annual meeting in statistical computing. His published work includes papers on time series, statistical computing, regression analysis, and statistical graphics and the book Data Analysis with Microsoft Excel (with Patrick Carey).

Patrick Carey received his M.S. in Biostatistics from the University of Wisconsin, where he worked as a researcher designing and analyzing clinical studies. He co-authored his first textbook on using Excel as a statistical tool. Patrick has authored or co-authored over 20 academic and trade texts for the software industry.

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Table of Contents

Chapter 1 Getting Started with Excel 1

Getting Started 2

Special Files for This Book 2

Installing the StatPlus Files 2

Excel and Spreadsheets 4

Launching Excel 5

Viewing the Excel Window 6

Running Excel Commands 7

Excel Workbooks and Worksheets 10

Opening a Workbook 10

Scrolling through a Workbook 11

Worksheet Cells 14

Selecting a Cell 14

Moving Cells 16

Printing from Excel 18

Previewing the Print Job 18

Setting Up the Page 19

Printing the Page 21

Saving Your Work 22

Excel Add-Ins 24

Loading the StatPlus Add-In 24

Loading the Data Analysis ToolPak 28

Unloading an Add-In 30

Features of StatPlus 30

Using StatPlus Modules 30

Hidden Data 31

Linked Formulas 32

Setup Options 32

Exiting Excel 34

Chapter 2 Working with Data 35

Data Entry 36

Entering Data from the Keyboard 36

Entering Data with Autofill 37

Inserting New Data 40

Data Formats 41

Formulas and Functions 45

Inserting a Simple Formula 46

Inserting an Excel Function 47

Cell References 50

Range Names 51

Sorting Data 54

Querying Data 55

Using the AutoFilter 56

Using the Advanced Filter 59

Using Calculated Values 62

Importing Data from Text Files 63

Importing Data from Databases 68

Using Excel's Database Query Wizard 68

Specifying Criteria and Sorting Data 71

Exercises 75

Chapter 3 Working with Charts 81

Introducing Excel Charts 82

Introducing Scatter Plots 86

Editing a Chart 91

Resizing and Moving an Embedded Chart 91

Moving a Chart to a Chart Sheet 93

Working with Chart and Axis Titles 94

Editing the Chart Axes 97

Working with Gridlines and Legends 100

Editing Plot Symbols 102

Identifying Data Points 105

Selecting aData Row 106

Labeling Data Points 107

Formatting Labels 109

Creating Bubble Plots 110

Breaking a Scatter Plot into Categories 117

Plotting Several Variables 120

Exercises 123

Chapter 4 Describing Your Data 128

Variables and Descriptive Statistics 129

Frequency Tables 131

Creating a Frequency Table 132

Using Bins in a Frequency Table 134

Defining Your Own Bin Values 136

Working with Histograms 138

Creating a Histogram 138

Shapes of Distributions 141

Breaking a Histogram into Categories 143

Working with Stem and Leaf Plots 146

Distribution Statistics 151

Percentiles and Quartiles 151

Measures of the Center: Means, Medians, and the Mode 154

Measures of Variability 159

Measures of Shape: Skewness and Kurtosis 162

Outliers 164

Working with Boxplots 165

Concept Tutorials: Boxplots 166

Exercises 175

Chapter 5 Probability Distributions 182

Probability 183

Probability Distributions 184

Discrete Probability Distributions 185

Continuous Probability Distributions 186

Concept Tutorials: PDFs 187

Random Variables and Random Samples 189

Concept Tutorials: Random Samples 190

The Normal Distribution 193

Concept Tutorials: The Normal Distribution 194

Excel Worksheet Functions 196

Using Excel to Generate Random Normal Data 197

Charting Random Normal Data 199

The Normal Probability Plot 201

Parameters and Estimators 205

The Sampling Distribution 206

Concept Tutorials: Sampling Distributions 211

The Standard Error 212

The Central Limit Theorem 212

Concept Tutorials: The Central Limit Theorem 213

Exercises 218

Chapter 6 Statistical Inference 224

Confidence Intervals 225

z Test Statistic and z Values 225

Calculating the Confidence Interval with Excel 228

Interpreting the Confidence Interval 229

Concept Tutorials: The Confidence Interval 229

Hypothesis Testing 232

Types of Error 233

An Example of Hypothesis Testing 234

Acceptance and Rejection Regions 234

p Values 235

Concept Tutorials: Hypothesis Testing 236

Additional Thoughts about Hypothesis Testing 239

The t Distribution 240

Concept Tutorials: The t Distribution 241

Working with the t Statistic 242

Constructing a t Confidence Interval 243

The Robustness of t 243

Applying the t Test to Paired Data 244

Applying a Nonparametric Test to Paired Data 250

The Wilcoxon Signed Rank Test 250

The Sign Test 253

The Two-Sample t Test 255

Comparing the Pooled and Unpooled Test Statistics 256

Working with the Two-Sample t Statistic 256

Testing for Equality of Variance 258

Applying the t Test to Two-Sample Data 259

Applying a Nonparametric Test to Two-Sample Data 265

Final Thoughts about Statistical Inference 267

Exercises 268

Chapter 7 Tables 275

PivotTables 276

Removing Categories from a PivotTable 280

Changing the Values Displayed by the PivotTable 282

Displaying Categorical Data in a Bar Chart 283

Displaying Categorical Data in a Pie Chart 285

Two-Way Tables 288

Computing Expected Counts 291

The Pearson Chi-Square Statistic 293

Concept Tutorials: The χ2 Distribution 293

Working with the χ2 Distribution in Excel 296

Breaking Down the Chi-Square Statistic 297

Other Table Statistics 297

Validity of the Chi-Square Test with Small Frequencies 299

Tables with Ordinal Variables 302

Testing for a Relationship between Two Ordinal Variables 303

Custom Sort Order 307

Exercises 309

Chapter 8 Regression and Correlation 313

Simple Linear Regression 314

The Regression Equation 314

Fitting the Regression Line 315

Regression Functions in Excel 316

Exploring Regression 317

Performing a Regression Analysis 318

Plotting Regression Data 320

Calculating Regression Statistics 323

Interpreting Regression Statistics 325

Interpreting the Analysis of Variance Table 326

Parameter Estimates and Statistics 327

Residuals and Predicted Values 328

Checking the Regression Model 329

Testing the Straight-Line Assumption 329

Testing for Normal Distribution of the Residuals 331

Testing for Constant Variance in the Residuals 332

Testing for the Independence of Residuals 332

Correlation 335

Correlation and Slope 336

Correlation and Causality 336

Spearman's Rank Correlation Coefficient s 337

Correlation Functions in Excel 337

Creating a Correlation Matrix 338

Correlation with a Two-Valued Variable 342

Adjusting Multiple p Values with Bonferroni 342

Creating a Scatter Plot Matrix 343

Exercises 345

Chapter 9 Multiple Regression 352

Regression Models with Multiple Parameters 353

Concept Tutorials: The F Distribution 353

Using Regression for Prediction 355

Regression Example: Predicting Grades 356

Interpreting the Regression Output 358

Multiple Correlation 359

Coefficients and the Prediction Equation 361

t Tests for the Coefficients 362

Testing Regression Assumptions 363

Observed versus Predicted Values 363

Plotting Residuals versus Predicted Values 366

Plotting Residuals versus Predictor Variables 368

Normal Errors and the Normal Plot 370

Summary of Calc Analysis 371

Regression Example: Sex Discrimination 371

Regression on Male Faculty 372

Using a SPLOM to See Relationships 373

Correlation Matrix of Variables 374

Multiple Regression 376

Interpreting the Regression Output 377

Residual Analysis of Discrimination Data 377

Normal Plot of Residuals 378

Are Female Faculty Underpaid? 380

Drawing Conclusions 385

Exercises 386

Chapter 10 Analysis of Variance 392

One-Way Analysis of Variance 393

Analysis of Variance Example: Comparing Hotel Prices 393

Graphing the Data to Verify ANOVA Assumptions 395

Computing the Analysis of Variance 397

Interpreting the Analysis of Variance Table 399

Comparing Means 402

Using the Bonferroni Correction Factor 403

When to Use Bonferroni 404

Comparing Means with a Boxplot 405

One-Way Analysis of Variance and Regression 406

Indicator Variables 406

Fitting the Effects Model 408

Two-Way Analysis of Variance 410

A Two-Factor Example 410

Two-Way Analysis Example: Comparing Soft Drinks 413

Graphing the Data to Verify Assumptions 414

The Interaction Plot 417

Using Excel to Perform a Two-Way Analysis of Variance 419

Interpreting the Analysis of Variance Table 422

Summary 424

Exercises 424

Chapter 11 Time Series 431

Time Series Concepts 432

Time Series Example: The Rise in Global Temperatures 432

Plotting the Global Temperature Time Series 433

Analyzing the Change in Global Temperature 436

Looking at Lagged Values 438

The Autocorrelation Function 440

Applying the ACF to Annual Mean Temperature 441

Other ACF Patterns 443

Applying the ACF to the Change in Temperature 444

Moving Averages 445

Simple Exponential Smoothing 448

Forecasting with Exponential Smoothing 450

Assessing the Accuracy of the Forecast 450

Concept Tutorials: One-Parameter Exponential Smoothing 451

Choosing a Value for w 455

Two-Parameter Exponential Smoothing 457

Calculating the Smoothed Values 458

Concept Tutorials: Two-Parameter Exponential Smoothing 459

Seasonality 462

Multiplicative Seasonality 462

Additive Seasonality 464

Seasonal Example: Liquor Sales 464

Examining Seasonality with a Boxplot 467

Examining Seasonality with a Line Plot 468

Applying the ACF to Seasonal Data 470

Adjusting for Seasonality 471

Three-Parameter Exponential Smoothing 473

Forecasting Liquor Sales 474

Optimizing the Exponential Smoothing Constant (optional) 479

Exercises 482

Chapter 12 Quality Control 487

Statistical Quality Control 488

Controlled Variation 489

Uncontrolled Variation 489

Control Charts 490

Control Charts and Hypothesis Testing 492

Variable and Attribute Charts 493

Using Subgroups 493

The <$>\bar {x}<$> Chart 493

Calculating Control Limits When σ Is Known 494

<$>\bar {x}<$> Chart Example: Teaching Scores 495

Calculating Control Limits When σ Is Unknown 498

<$>\bar {x}<$> Chart Example: A Coating Process 500

The Range Chart 502

The C Chart 504

C Chart Example: Factory Accidents 504

The P Chart 506

P Chart Example: Steel Rod Defects 507

Control Charts for Individual Observations 509

The Pareto Chart 513

Exercises 517

Appendix 521

Excel Reference 581

Bibliography 587

Index 589

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