Data Analysis with Microsoft Excel™ Updated for Office 2007 (Book Only)

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  • Edition: 3rd
  • Format: Paperback
  • Copyright: 6/18/2009
  • Publisher: Cengage Learning

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This popular best-selling book shows students and professionals how to do data analysis with Microsoft? Excel. DATA ANALYSIS WITH MICROSOFT EXCEL teaches the fundamental concepts of statistics and how to use Microsoft Excel to solve the kind of data-intensive problems that arise in business and elsewhere. Even students with no previous experience using spreadsheets will find that this text?s step-by-step approach, extensive tutorials, and examples make it easy to learn how to use Excel for analyzing data. A downloadable StatPlus? add-in for Microsoft Excel, data sets for exercises, and interactive concept tutorials are available on the Book Companion Website.

Table of Contents

Getting Started with Excelp. 1
Getting Startedp. 2
Special Files for This Bookp. 2
Installing the StatPlus Filesp. 2
Excel and Spreadsheetsp. 4
Launching Excelp. 5
Viewing the Excel Windowp. 6
Running Excel Commandsp. 7
Excel Workbooks and Worksheetsp. 10
Opening a Workbookp. 10
Scrolling through a Workbookp. 11
Worksheet Cellsp. 14
Selecting a Cellp. 14
Moving Cellsp. 16
Printing from Excelp. 18
Previewing the Print Jobp. 18
Setting Up the Pagep. 19
Printing the Pagep. 21
Saving Your Workp. 22
Excel Add-Insp. 24
Loading the StatPlus Add-Inp. 24
Loading the Data Analysis ToolPakp. 28
Unloading an Add-Inp. 30
Features of StatPlusp. 30
Using StatPlus Modulesp. 30
Hidden Datap. 31
Linked Formulasp. 32
Setup Optionsp. 32
Exiting Excelp. 34
Working with Datap. 35
Data Entryp. 36
Entering Data from the Keyboardp. 36
Entering Data with Autofillp. 37
Inserting New Datap. 40
Data Formatsp. 41
Formulas and Functionsp. 45
Inserting a Simple Formulap. 46
Inserting an Excel Functionp. 47
Cell Referencesp. 50
Range Namesp. 51
Sorting Datap. 54
Querying Datap. 55
Using the AutoFilterp. 56
Using the Advanced Filterp. 59
Using Calculated Valuesp. 62
Importing Data from Text Filesp. 63
Importing Data from Databasesp. 68
Using Excel's Database Query Wizardp. 68
Specifying Criteria and Sorting Datap. 71
Exercisesp. 75
Working with Chartsp. 81
Introducing Excel Chartsp. 82
Introducing Scatter Plotsp. 86
Editing a Chartp. 91
Resizing and Moving an Embedded Chartp. 91
Moving a Chart to a Chart Sheetp. 93
Working with Chart and Axis Titlesp. 94
Editing the Chart Axesp. 97
Working with Gridlines and Legendsp. 100
Editing Plot Symbolsp. 102
Identifying Data Pointsp. 105
Selecting a Data Rowp. 106
Labeling Data Pointsp. 107
Formatting Labelsp. 109
Creating Bubble Plotsp. 110
Breaking a Scatter Plot into Categoriesp. 117
Plotting Several Variablesp. 120
Exercisesp. 123
Describing Your Datap. 128
Variables and Descriptive Statisticsp. 129
Frequency Tablesp. 131
Creating a Frequency Tablep. 132
Using Bins in a Frequency Tablep. 134
Defining Your Own Bin Valuesp. 136
Working with Histogramsp. 138
Creating a Histogramp. 138
Shapes of Distributionsp. 141
Breaking a Histogram into Categoriesp. 143
Working with Stem and Leaf Plotsp. 146
Distribution Statisticsp. 151
Percentiles and Quartilesp. 151
Measures of the Center: Means, Medians, and the Modep. 154
Measures of Variabilityp. 159
Measures of Shape: Skewness and Kurtosisp. 162
Outliersp. 164
Working with Boxplotsp. 165
Concept Tutorials: Boxplotsp. 166
Exercisesp. 175
Probability Distributionsp. 182
Probabilityp. 183
Probability Distributionsp. 184
Discrete Probability Distributionsp. 185
Continuous Probability Distributionsp. 186
Concept Tutorials: PDFsp. 187
Random Variables and Random Samplesp. 189
Concept Tutorials: Random Samplesp. 190
The Normal Distributionp. 193
Concept Tutorials: The Normal Distributionp. 194
Excel Worksheet Functionsp. 196
Using Excel to Generate Random Normal Datap. 197
Charting Random Normal Datap. 199
The Normal Probability Plotp. 201
Parameters and Estimatorsp. 205
The Sampling Distributionp. 206
Concept Tutorials: Sampling Distributionsp. 211
The Standard Errorp. 212
The Central Limit Theoremp. 212
Concept Tutorials: The Central Limit Theoremp. 213
Exercisesp. 218
Statistical Inferencep. 224
Confidence Intervalsp. 225
z Test Statistic and z Valuesp. 225
Calculating the Confidence Interval with Excelp. 228
Interpreting the Confidence Intervalp. 229
Concept Tutorials: The Confidence Intervalp. 229
Hypothesis Testingp. 232
Types of Errorp. 233
An Example of Hypothesis Testingp. 234
Acceptance and Rejection Regionsp. 234
p Valuesp. 235
Concept Tutorials: Hypothesis Testingp. 236
Additional Thoughts about Hypothesis Testingp. 239
The t Distributionp. 240
Concept Tutorials: The t Distributionp. 241
Working with the t Statisticp. 242
Constructing a t Confidence Intervalp. 243
The Robustness of tp. 243
Applying the t Test to Paired Datap. 244
Applying a Nonparametric Test to Paired Datap. 250
The Wilcoxon Signed Rank Testp. 250
The Sign Testp. 253
The Two-Sample t Testp. 255
Comparing the Pooled and Unpooled Test Statisticsp. 256
Working with the Two-Sample t Statisticp. 256
Testing for Equality of Variancep. 258
Applying the t Test to Two-Sample Datap. 259
Applying a Nonparametric Test to Two-Sample Datap. 265
Final Thoughts about Statistical Inferencep. 267
Exercisesp. 268
Tablesp. 275
PivotTablesp. 276
Removing Categories from a PivotTablep. 280
Changing the Values Displayed by the PivotTablep. 282
Displaying Categorical Data in a Bar Chartp. 283
Displaying Categorical Data in a Pie Chartp. 285
Two-Way Tablesp. 288
Computing Expected Countsp. 291
The Pearson Chi-Square Statisticp. 293
Concept Tutorials: The ¿2 Distributionp. 293
Working with the ¿2 Distribution in Excelp. 296
Breaking Down the Chi-Square Statisticp. 297
Other Table Statisticsp. 297
Validity of the Chi-Square Test with Small Frequenciesp. 299
Tables with Ordinal Variablesp. 302
Testing for a Relationship between Two Ordinal Variablesp. 303
Custom Sort Orderp. 307
Exercisesp. 309
Regression and Correlationp. 313
Simple Linear Regressionp. 314
The Regression Equationp. 314
Fitting the Regression Linep. 315
Regression Functions in Excelp. 316
Exploring Regressionp. 317
Performing a Regression Analysisp. 318
Plotting Regression Datap. 320
Calculating Regression Statisticsp. 323
Interpreting Regression Statisticsp. 325
Interpreting the Analysis of Variance Tablep. 326
Parameter Estimates and Statisticsp. 327
Residuals and Predicted Valuesp. 328
Checking the Regression Modelp. 329
Testing the Straight-Line Assumptionp. 329
Testing for Normal Distribution of the Residualsp. 331
Testing for Constant Variance in the Residualsp. 332
Testing for the Independence of Residualsp. 332
Correlationp. 335
Correlation and Slopep. 336
Correlation and Causalityp. 336
Spearman's Rank Correlation Coefficient sp. 337
Correlation Functions in Excelp. 337
Creating a Correlation Matrixp. 338
Correlation with a Two-Valued Variablep. 342
Adjusting Multiple p Values with Bonferronip. 342
Creating a Scatter Plot Matrixp. 343
Exercisesp. 345
Multiple Regressionp. 352
Regression Models with Multiple Parametersp. 353
Concept Tutorials: The F Distributionp. 353
Using Regression for Predictionp. 355
Regression Example: Predicting Gradesp. 356
Interpreting the Regression Outputp. 358
Multiple Correlationp. 359
Coefficients and the Prediction Equationp. 361
t Tests for the Coefficientsp. 362
Testing Regression Assumptionsp. 363
Observed versus Predicted Valuesp. 363
Plotting Residuals versus Predicted Valuesp. 366
Plotting Residuals versus Predictor Variablesp. 368
Normal Errors and the Normal Plotp. 370
Summary of Calc Analysisp. 371
Regression Example: Sex Discriminationp. 371
Regression on Male Facultyp. 372
Using a SPLOM to See Relationshipsp. 373
Correlation Matrix of Variablesp. 374
Multiple Regressionp. 376
Interpreting the Regression Outputp. 377
Residual Analysis of Discrimination Datap. 377
Normal Plot of Residualsp. 378
Are Female Faculty Underpaid?p. 380
Drawing Conclusionsp. 385
Exercisesp. 386
Analysis of Variancep. 392
One-Way Analysis of Variancep. 393
Analysis of Variance Example: Comparing Hotel Pricesp. 393
Graphing the Data to Verify ANOVA Assumptionsp. 395
Computing the Analysis of Variancep. 397
Interpreting the Analysis of Variance Tablep. 399
Comparing Meansp. 402
Using the Bonferroni Correction Factorp. 403
When to Use Bonferronip. 404
Comparing Means with a Boxplotp. 405
One-Way Analysis of Variance and Regressionp. 406
Indicator Variablesp. 406
Fitting the Effects Modelp. 408
Two-Way Analysis of Variancep. 410
A Two-Factor Examplep. 410
Two-Way Analysis Example: Comparing Soft Drinksp. 413
Graphing the Data to Verify Assumptionsp. 414
The Interaction Plotp. 417
Using Excel to Perform a Two-Way Analysis of Variancep. 419
Interpreting the Analysis of Variance Tablep. 422
Summaryp. 424
Exercisesp. 424
Time Seriesp. 431
Time Series Conceptsp. 432
Time Series Example: The Rise in Global Temperaturesp. 432
Plotting the Global Temperature Time Seriesp. 433
Analyzing the Change in Global Temperaturep. 436
Looking at Lagged Valuesp. 438
The Autocorrelation Functionp. 440
Applying the ACF to Annual Mean Temperaturep. 441
Other ACF Patternsp. 443
Applying the ACF to the Change in Temperaturep. 444
Moving Averagesp. 445
Simple Exponential Smoothingp. 448
Forecasting with Exponential Smoothingp. 450
Assessing the Accuracy of the Forecastp. 450
Concept Tutorials: One-Parameter Exponential Smoothingp. 451
Choosing a Value for wp. 455
Two-Parameter Exponential Smoothingp. 457
Calculating the Smoothed Valuesp. 458
Concept Tutorials: Two-Parameter Exponential Smoothingp. 459
Seasonalityp. 462
Multiplicative Seasonalityp. 462
Additive Seasonalityp. 464
Seasonal Example: Liquor Salesp. 464
Examining Seasonality with a Boxplotp. 467
Examining Seasonality with a Line Plotp. 468
Applying the ACF to Seasonal Datap. 470
Adjusting for Seasonalityp. 471
Three-Parameter Exponential Smoothingp. 473
Forecasting Liquor Salesp. 474
Optimizing the Exponential Smoothing Constant (optional)p. 479
Exercisesp. 482
Quality Controlp. 487
Statistical Quality Controlp. 488
Controlled Variationp. 489
Uncontrolled Variationp. 489
Control Chartsp. 490
Control Charts and Hypothesis Testingp. 492
Variable and Attribute Chartsp. 493
Using Subgroupsp. 493
The <$>\bar {x}<$> Chartp. 493
Calculating Control Limits When ¿ Is Knownp. 494
<$>\bar {x}<$> Chart Example: Teaching Scoresp. 495
Calculating Control Limits When ¿ Is Unknownp. 498
<$>\bar {x}<$> Chart Example: A Coating Processp. 500
The Range Chartp. 502
The C Chartp. 504
C Chart Example: Factory Accidentsp. 504
The P Chartp. 506
P Chart Example: Steel Rod Defectsp. 507
Control Charts for Individual Observationsp. 509
The Pareto Chartp. 513
Exercisesp. 517
Appendixp. 521
Excel Referencep. 581
Bibliographyp. 587
Indexp. 589
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