Data Analysis with Microsoft Excel Updated for Office XP

ISBN-10: 0534407145

ISBN-13: 9780534407148

Edition: 2nd 2004 (Revised)

List price: $153.95
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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 students and professionals 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 CD-ROM is included with every new text that contains the StatPlus add-ins for Microsoft Excel and data sets for exercises.
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Book details

List price: $153.95
Edition: 2nd
Copyright year: 2004
Publisher: Brooks/Cole
Publication date: 3/25/2003
Binding: Paperback
Pages: 600
Size: 7.50" wide x 9.50" long x 1.00" tall
Weight: 0.880

Jay Devore received a B.S. in Engineering Science from the University of California, Berkeley, and a Ph.D. in Statistics from Stanford University. He previously taught at the University of Florida and Oberlin College, and has had visiting positions at Stanford, Harvard, the University of Washington, New York University, and Columbia. He has been at California Polytechnic State University, San Luis Obispo, since 1977, where he was chair of the Department of Statistics for seven years and recently achieved the exalted status of Professor Emeritus.Jay has previously authored or coauthored �ve other books, including Probability and Statistics for Engineering and the Sciences, which won a McGuffey Longevity Award from the Text and Academic Authors Association for demonstrated excellence over time . He is a Fellow of the American Statistical Association, has been an associate editor for both the Journal of the American Statistical Association and The American Statistician, and received the Distinguished Teaching Award from Cal Poly in 1991. His recreational interests include reading, playing tennis, traveling, and cooking and eating good food.Ken Berk has a B.S. in Physics from Carnegie Tech (now Carnegie Mellon) and a Ph.D. in Mathematics from the University of 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, as well as 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 in the General Clinical Research Center designing and analyzing clinical studies. He co-authored his first textbook with Kenneth Berk on using Excel as a statistical tool. He and his wife Joan founded Carey Associates, Inc., a software textbook development company. He has since authored or co-authored over 20 academic and trade texts for the software industry. Besides books on data analysis, Carey has written on the Windows operating system, Web page design, database management, the Internet, browsers, and presentation graphics software. Patrick, Joan, and their six children live in Madison, Wisconsin.

Getting Started with Excel
The Windows Operating System
Special Files for this Book
Excel and Spreadsheets
Excel Workbooks and Worksheets
Worksheet Cells
Printing from Excel
Saving Your Work
Excel Add-Ins
Features of Statplus
Exiting Excel
Working with Data
Data entry
Data Formats
Formulas and Functions
Cell references
Range Names
Sorting Data
Querying Data
Importing Data from Text Files
Importing Data from Databases
Working with Charts
Working with Excel Charts
Introducing Scatterplots
Creating Charts with the Chart Wizard
Editing a Chart
Identifying Data Points
Creating Bubble Plots
Breaking a Scatterplot into Categories
Plotting Several Variables
Fundamentals Of Statistics
Describing Your Data
Variables and Descriptive Statistics
Looking at Distributions with Frequency Tables
Working with Histograms
Working with Stem and Leaf Plots
Distribution Statistics
Working with Boxplots
Probability Distributions
Probability Distributions
Random Variables and Random Samples
The Normal Distribution
Parameters and Estimators
The Sampling Distribution
The Central Limit Theorem
Statistical Inference
Confidence Intervals
Hypothesis Testing
The t-Distribution
Applying the t-Test to Paired Data
Applying a Non-parametric Test to Paired Data
The Two-Sample t-Test
Applying the t-Test to Two-Sample Data
Applying a Nonparametric Test to Two-Sample Data
Final Thoughts about Statistical Inference
Pivot tables
Two-Way Tables
Computing Expected Counts
The Pearson Chi-Square Statistic
Other Table Statistics
Validity of the Chi-Square Test with Small Frequencies
Tables with Ordinal Variables
Statistical Methods
Regression and Correlation
Simple Linear Regression
Regression Functions in Excel
Performing a Regression on Analysis
Checking the Regression Model
Creating a Correlation Matrix
Creating a Scatterplot Matrix
Multiple Regression
Regression Models with Multiple Parameters
Regression Example: Predicting Grades
Testing Regression Assumptions
Plotting Residuals s
Predicted Values
Regression Example: Sex Discrimination
Analysis of Variance
One-Way Analysis of Variance
Analysis of Variance Example: Comparing Hotel Prices
Comparing Means
Using the Bonferroni Correction Factor
When to Use Bonferroni
One-Way Analysis of Variance and Regression
Two-Way Analysis of Variance
A Two-Factor Example
Two-Way Analysis Example: Comparing Soft Drinks
Time Series
Time Series Concepts
Time Series Example: The Dow in the 1980s
The Autocorrelation Function
Moving Averages
Simple Exponential Smoothing
Two-Parameter Exponential Smoothing
Seasonal Example: Beer Production
Three-Parameter Exponential
Optimizing the Exponential
Smoothing Constant (optional)
Quality Control
Statistical Quality Control
Control Charts
The Chi [overbar] Chart
The Range Chart
The C-Chart
The P-Chart
Control Charts for Individual Observations
The Pareto Chart
Excel Reference
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