The Excel 2007 Data and Statistics Cookbook
Author : Larry Pace
Publisher :
Page : pages
File Size : 20,91 MB
Release : 2007-09-01
Category :
ISBN : 9780979977510
Author : Larry Pace
Publisher :
Page : pages
File Size : 20,91 MB
Release : 2007-09-01
Category :
ISBN : 9780979977510
Author : Larry Pace
Publisher : Lulu.com
Page : 207 pages
File Size : 44,51 MB
Release : 2012-11-12
Category : Computers
ISBN : 0988630001
The Excel Data and Statistics Cookbook,3rd edition, covers all the basic descriptive and inferential statistics taught in an introductory class. Completely updated to illustrate Excel 2013, 2011 (for Mac), and 2010, this book is classroom-tested and instructor-approved.
Author : Larry Alton Pace
Publisher :
Page : 132 pages
File Size : 44,44 MB
Release : 2008-01-01
Category : Electronic data processing
ISBN : 9780979977527
Provides point-and-click access to the most common basic descriptive and inferential statistics. Topics include: the Excel 2007 interface, data management features of Excel 2007, tables and pivot tables, descriptive statistics, charts and graphs, working with z scores and the normal distribution, installing and using the analysis toolpak, one-sample t tests, paired-samples t tests, independent-samples t tests, one-way ANOVA, repeated-measures ANOVA, correlation and regression, Chi-square tests, post hoc comparisons, and effect size.
Author : Larry Alton Pace
Publisher :
Page : 0 pages
File Size : 39,61 MB
Release : 2011
Category : Electronic spreadsheets
ISBN : 9780205840670
"Over the past several years, there has been an increased interest in the use of spreadsheets for teaching and learning basic statistics. This movement began in business schools, where spreadsheets are used extensively, but has recently expanded to the sciences and more recently, the social sciences. This book about using a widely available spreadsheet program for basic statistics can be used as a course supplement or as a standalone text. Topics covered include those commonly taught in a first course (or two-course sequence) in basic descriptive and inferential statistics. Although the text makes repeated use of certain datasets, each chapter serves as a standalone module, so instructors can skip the topics they do not wish to cover."--Publisher's website.
Author : Harvey Motulsky
Publisher : Oxford University Press, USA
Page : 508 pages
File Size : 27,84 MB
Release : 2010
Category : Medical
ISBN : 0199730067
Thoroughly revised and updated, the second edition of Intuitive Biostatistics retains and refines the core perspectives of the previous edition: a focus on how to interpret statistical results rather than on how to analyze data, minimal use of equations, and a detailed review of assumptions and common mistakes. Intuitive Biostatistics, Completely Revised Second Edition, provides a clear introduction to statistics for undergraduate and graduate students and also serves as a statistics refresher for working scientists.
Author : Larry Pace
Publisher : Apress
Page : 322 pages
File Size : 17,39 MB
Release : 2012-11-28
Category : Computers
ISBN : 1430245557
Beginning R: An Introduction to Statistical Programming is a hands-on book showing how to use the R language, write and save R scripts, build and import data files, and write your own custom statistical functions. R is a powerful open-source implementation of the statistical language S, which was developed by AT&T. R has eclipsed S and the commercially-available S-Plus language, and has become the de facto standard for doing, teaching, and learning computational statistics. R is both an object-oriented language and a functional language that is easy to learn, easy to use, and completely free. A large community of dedicated R users and programmers provides an excellent source of R code, functions, and data sets. R is also becoming adopted into commercial tools such as Oracle Database. Your investment in learning R is sure to pay off in the long term as R continues to grow into the go to language for statistical exploration and research. Covers the freely-available R language for statistics Shows the use of R in specific uses case such as simulations, discrete probability solutions, one-way ANOVA analysis, and more Takes a hands-on and example-based approach incorporating best practices with clear explanations of the statistics being done
Author : Ken Bluttman
Publisher : "O'Reilly Media, Inc."
Page : 369 pages
File Size : 31,56 MB
Release : 2007-05-14
Category : Computers
ISBN : 0596555210
If you have large quantities of data in a Microsoft Access database, and need to study that data in depth, this book is a data cruncher's dream. Access Data Analysis Cookbook offers practical recipes to solve a variety of common problems that users have with extracting Access data and performing calculations on it. Each recipe includes a discussion on how and why the solution works. Whether you use Access 2007 or an earlier version, this book will teach you new methods to query data, different ways to move data in and out of Access, how to calculate answers to financial and investment issues, and more. Learn how to apply statistics to summarize business information, how to jump beyond SQL by manipulating data with VBA, how to process dates and times, and even how to reach into the Excel data analysis toolkit. Recipes demonstrate ways to: Develop basic and sophisticated queries Apply aggregate functions, custom functions, regular expressions, and crosstabs Apply queries to perform non-passive activities such as inserting, updating, and deleting data Create and manipulate tables and queries programmatically Manage text-based data, including methods to isolate parts of a string and ways to work with numbers that are stored as text Use arrays, read and write to the Windows registry, encrypt data, and use transaction processing Use the FileSystemObject, use XML with XSLT, communicate with SQL Server, and exchange data with other Office products Find answers from time-based data, such as how to add time, count elapsed time, work with leap years, and how to manage time zones in your calculations Deal with business and finance problems, including methods for calculating depreciation, loan paybacks, and Return on Investment (ROI) Explore statistical techniques, such as frequency, variance, kurtosis, linear regression, combinations and permutations Access Data Analysis Cookbook is a one-stop-shop for extracting nuggets of valuable information from your database, and anyone with Access experience will benefit from these tips and techniques, including seasoned developers. If you want to use your data, and not just store it, you'll find this guide indispensable.
Author : Winston Chang
Publisher : "O'Reilly Media, Inc."
Page : 414 pages
File Size : 35,47 MB
Release : 2013
Category : Computers
ISBN : 1449316956
"Practical recipes for visualizing data"--Cover.
Author : Stephen L. Nelson
Publisher : John Wiley & Sons
Page : 359 pages
File Size : 20,41 MB
Release : 2011-02-09
Category : Computers
ISBN : 1118051351
Shows ordinary users how to tap the rich data analysis functionality of Excel, make sense of their organization's critical financial and statistical information, and put together compelling data presentations Now revised with over 30 percent new content to cover the enhancements in Excel 2007, including the completely redesigned user interface, augmented charting and PivotTable capabilities, improved security, and better data exchange through XML Provides thorough coverage of Excel features that are critical to data analysis-working with external databases, creating PivotTables and PivotCharts, using Excel statistical and financial functions, sharing data, harnessing the Solver, taking advantage of the Small Business Finance Manager, and more
Author : Richard M. Heiberger
Publisher : Springer Science & Business Media
Page : 357 pages
File Size : 44,23 MB
Release : 2010-01-23
Category : Computers
ISBN : 1441900527
In this book, the authors build on RExcel, a free add-in for Excel that can be downloaded from the R distribution network. RExcel seamlessly integrates the entire set of R's statistical and graphical methods into Excel, allowing students to focus on statistical methods and concepts and minimizing the distraction of learning a new programming language.