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

by ;
Edition:
3rd
ISBN13:

ISBN10:
0495391786
Format:
Paperback
Pub. Date:
6/18/2009
Publisher(s):
Cengage Learning
List Price: $138.95 ## Rent Textbook (Recommended) Term Due Price$104.21

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What version or edition is this?
This is the 3rd edition with a publication date of 6/18/2009.
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## Summary

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.

 Getting Started with Excel p. 1 Getting Started p. 2 Special Files for This Book p. 2 Installing the StatPlus Files p. 2 Excel and Spreadsheets p. 4 Launching Excel p. 5 Viewing the Excel Window p. 6 Running Excel Commands p. 7 Excel Workbooks and Worksheets p. 10 Opening a Workbook p. 10 Scrolling through a Workbook p. 11 Worksheet Cells p. 14 Selecting a Cell p. 14 Moving Cells p. 16 Printing from Excel p. 18 Previewing the Print Job p. 18 Setting Up the Page p. 19 Printing the Page p. 21 Saving Your Work p. 22 Excel Add-Ins p. 24 Loading the StatPlus Add-In p. 24 Loading the Data Analysis ToolPak p. 28 Unloading an Add-In p. 30 Features of StatPlus p. 30 Using StatPlus Modules p. 30 Hidden Data p. 31 Linked Formulas p. 32 Setup Options p. 32 Exiting Excel p. 34 Working with Data p. 35 Data Entry p. 36 Entering Data from the Keyboard p. 36 Entering Data with Autofill p. 37 Inserting New Data p. 40 Data Formats p. 41 Formulas and Functions p. 45 Inserting a Simple Formula p. 46 Inserting an Excel Function p. 47 Cell References p. 50 Range Names p. 51 Sorting Data p. 54 Querying Data p. 55 Using the AutoFilter p. 56 Using the Advanced Filter p. 59 Using Calculated Values p. 62 Importing Data from Text Files p. 63 Importing Data from Databases p. 68 Using Excel's Database Query Wizard p. 68 Specifying Criteria and Sorting Data p. 71 Exercises p. 75 Working with Charts p. 81 Introducing Excel Charts p. 82 Introducing Scatter Plots p. 86 Editing a Chart p. 91 Resizing and Moving an Embedded Chart p. 91 Moving a Chart to a Chart Sheet p. 93 Working with Chart and Axis Titles p. 94 Editing the Chart Axes p. 97 Working with Gridlines and Legends p. 100 Editing Plot Symbols p. 102 Identifying Data Points p. 105 Selecting a Data Row p. 106 Labeling Data Points p. 107 Formatting Labels p. 109 Creating Bubble Plots p. 110 Breaking a Scatter Plot into Categories p. 117 Plotting Several Variables p. 120 Exercises p. 123 Describing Your Data p. 128 Variables and Descriptive Statistics p. 129 Frequency Tables p. 131 Creating a Frequency Table p. 132 Using Bins in a Frequency Table p. 134 Defining Your Own Bin Values p. 136 Working with Histograms p. 138 Creating a Histogram p. 138 Shapes of Distributions p. 141 Breaking a Histogram into Categories p. 143 Working with Stem and Leaf Plots p. 146 Distribution Statistics p. 151 Percentiles and Quartiles p. 151 Measures of the Center: Means, Medians, and the Mode p. 154 Measures of Variability p. 159 Measures of Shape: Skewness and Kurtosis p. 162 Outliers p. 164 Working with Boxplots p. 165 Concept Tutorials: Boxplots p. 166 Exercises p. 175 Probability Distributions p. 182 Probability p. 183 Probability Distributions p. 184 Discrete Probability Distributions p. 185 Continuous Probability Distributions p. 186 Concept Tutorials: PDFs p. 187 Random Variables and Random Samples p. 189 Concept Tutorials: Random Samples p. 190 The Normal Distribution p. 193 Concept Tutorials: The Normal Distribution p. 194 Excel Worksheet Functions p. 196 Using Excel to Generate Random Normal Data p. 197 Charting Random Normal Data p. 199 The Normal Probability Plot p. 201 Parameters and Estimators p. 205 The Sampling Distribution p. 206 Concept Tutorials: Sampling Distributions p. 211 The Standard Error p. 212 The Central Limit Theorem p. 212 Concept Tutorials: The Central Limit Theorem p. 213 Exercises p. 218 Statistical Inference p. 224 Confidence Intervals p. 225 z Test Statistic and z Values p. 225 Calculating the Confidence Interval with Excel p. 228 Interpreting the Confidence Interval p. 229 Concept Tutorials: The Confidence Interval p. 229 Hypothesis Testing p. 232 Types of Error p. 233 An Example of Hypothesis Testing p. 234 Acceptance and Rejection Regions p. 234 p Values p. 235 Concept Tutorials: Hypothesis Testing p. 236 Additional Thoughts about Hypothesis Testing p. 239 The t Distribution p. 240 Concept Tutorials: The t Distribution p. 241 Working with the t Statistic p. 242 Constructing a t Confidence Interval p. 243 The Robustness of t p. 243 Applying the t Test to Paired Data p. 244 Applying a Nonparametric Test to Paired Data p. 250 The Wilcoxon Signed Rank Test p. 250 The Sign Test p. 253 The Two-Sample t Test p. 255 Comparing the Pooled and Unpooled Test Statistics p. 256 Working with the Two-Sample t Statistic p. 256 Testing for Equality of Variance p. 258 Applying the t Test to Two-Sample Data p. 259 Applying a Nonparametric Test to Two-Sample Data p. 265 Final Thoughts about Statistical Inference p. 267 Exercises p. 268 Tables p. 275 PivotTables p. 276 Removing Categories from a PivotTable p. 280 Changing the Values Displayed by the PivotTable p. 282 Displaying Categorical Data in a Bar Chart p. 283 Displaying Categorical Data in a Pie Chart p. 285 Two-Way Tables p. 288 Computing Expected Counts p. 291 The Pearson Chi-Square Statistic p. 293 Concept Tutorials: The ¿2 Distribution p. 293 Working with the ¿2 Distribution in Excel p. 296 Breaking Down the Chi-Square Statistic p. 297 Other Table Statistics p. 297 Validity of the Chi-Square Test with Small Frequencies p. 299 Tables with Ordinal Variables p. 302 Testing for a Relationship between Two Ordinal Variables p. 303 Custom Sort Order p. 307 Exercises p. 309 Regression and Correlation p. 313 Simple Linear Regression p. 314 The Regression Equation p. 314 Fitting the Regression Line p. 315 Regression Functions in Excel p. 316 Exploring Regression p. 317 Performing a Regression Analysis p. 318 Plotting Regression Data p. 320 Calculating Regression Statistics p. 323 Interpreting Regression Statistics p. 325 Interpreting the Analysis of Variance Table p. 326 Parameter Estimates and Statistics p. 327 Residuals and Predicted Values p. 328 Checking the Regression Model p. 329 Testing the Straight-Line Assumption p. 329 Testing for Normal Distribution of the Residuals p. 331 Testing for Constant Variance in the Residuals p. 332 Testing for the Independence of Residuals p. 332 Correlation p. 335 Correlation and Slope p. 336 Correlation and Causality p. 336 Spearman's Rank Correlation Coefficient s p. 337 Correlation Functions in Excel p. 337 Creating a Correlation Matrix p. 338 Correlation with a Two-Valued Variable p. 342 Adjusting Multiple p Values with Bonferroni p. 342 Creating a Scatter Plot Matrix p. 343 Exercises p. 345 Multiple Regression p. 352 Regression Models with Multiple Parameters p. 353 Concept Tutorials: The F Distribution p. 353 Using Regression for Prediction p. 355 Regression Example: Predicting Grades p. 356 Interpreting the Regression Output p. 358 Multiple Correlation p. 359 Coefficients and the Prediction Equation p. 361 t Tests for the Coefficients p. 362 Testing Regression Assumptions p. 363 Observed versus Predicted Values p. 363 Plotting Residuals versus Predicted Values p. 366 Plotting Residuals versus Predictor Variables p. 368 Normal Errors and the Normal Plot p. 370 Summary of Calc Analysis p. 371 Regression Example: Sex Discrimination p. 371 Regression on Male Faculty p. 372 Using a SPLOM to See Relationships p. 373 Correlation Matrix of Variables p. 374 Multiple Regression p. 376 Interpreting the Regression Output p. 377 Residual Analysis of Discrimination Data p. 377 Normal Plot of Residuals p. 378 Are Female Faculty Underpaid? p. 380 Drawing Conclusions p. 385 Exercises p. 386 Analysis of Variance p. 392 One-Way Analysis of Variance p. 393 Analysis of Variance Example: Comparing Hotel Prices p. 393 Graphing the Data to Verify ANOVA Assumptions p. 395 Computing the Analysis of Variance p. 397 Interpreting the Analysis of Variance Table p. 399 Comparing Means p. 402 Using the Bonferroni Correction Factor p. 403 When to Use Bonferroni p. 404 Comparing Means with a Boxplot p. 405 One-Way Analysis of Variance and Regression p. 406 Indicator Variables p. 406 Fitting the Effects Model p. 408 Two-Way Analysis of Variance p. 410 A Two-Factor Example p. 410 Two-Way Analysis Example: Comparing Soft Drinks p. 413 Graphing the Data to Verify Assumptions p. 414 The Interaction Plot p. 417 Using Excel to Perform a Two-Way Analysis of Variance p. 419 Interpreting the Analysis of Variance Table p. 422 Summary p. 424 Exercises p. 424 Time Series p. 431 Time Series Concepts p. 432 Time Series Example: The Rise in Global Temperatures p. 432 Plotting the Global Temperature Time Series p. 433 Analyzing the Change in Global Temperature p. 436 Looking at Lagged Values p. 438 The Autocorrelation Function p. 440 Applying the ACF to Annual Mean Temperature p. 441 Other ACF Patterns p. 443 Applying the ACF to the Change in Temperature p. 444 Moving Averages p. 445 Simple Exponential Smoothing p. 448 Forecasting with Exponential Smoothing p. 450 Assessing the Accuracy of the Forecast p. 450 Concept Tutorials: One-Parameter Exponential Smoothing p. 451 Choosing a Value for w p. 455 Two-Parameter Exponential Smoothing p. 457 Calculating the Smoothed Values p. 458 Concept Tutorials: Two-Parameter Exponential Smoothing p. 459 Seasonality p. 462 Multiplicative Seasonality p. 462 Additive Seasonality p. 464 Seasonal Example: Liquor Sales p. 464 Examining Seasonality with a Boxplot p. 467 Examining Seasonality with a Line Plot p. 468 Applying the ACF to Seasonal Data p. 470 Adjusting for Seasonality p. 471 Three-Parameter Exponential Smoothing p. 473 Forecasting Liquor Sales p. 474 Optimizing the Exponential Smoothing Constant (optional) p. 479 Exercises p. 482 Quality Control p. 487 Statistical Quality Control p. 488 Controlled Variation p. 489 Uncontrolled Variation p. 489 Control Charts p. 490 Control Charts and Hypothesis Testing p. 492 Variable and Attribute Charts p. 493 Using Subgroups p. 493 The <$>\bar {x}<$> Chart p. 493 Calculating Control Limits When ¿ Is Known p. 494 <$>\bar {x}<$> Chart Example: Teaching Scores p. 495 Calculating Control Limits When ¿ Is Unknown p. 498 <$>\bar {x}<$> Chart Example: A Coating Process p. 500 The Range Chart p. 502 The C Chart p. 504 C Chart Example: Factory Accidents p. 504 The P Chart p. 506 P Chart Example: Steel Rod Defects p. 507 Control Charts for Individual Observations p. 509 The Pareto Chart p. 513 Exercises p. 517 Appendix p. 521 Excel Reference p. 581 Bibliography p. 587 Index p. 589 Table of Contents provided by Ingram. 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