Managing Data Using Excel
Published on 23. February 2015
Book
Paperback/Softback
326 pages
978-1-78427-007-0 (ISBN)
Description
Microsoft Excel is a powerful tool that can transform the way you use data. This book explains in comprehensive and user-friendly detail how to manage, make sense of, explore and share data, giving scientists at all levels the skills they need to maximize the usefulness of their data.
Readers will learn how to use Excel to:
* Build a dataset - how to handle variables and notes, rearrangements and edits to data.
* Check datasets - dealing with typographic errors, data validation and numerical
errors.
* Make sense of data - including datasets for regression and correlation; summarizing data with averages and variability; and visualizing data with graphs, pivot charts and sparklines.
* Explore regression data - finding, highlighting and visualizing correlations.
* Explore time-related data - using pivot tables, sparklines and line plots.
* Explore association data - creating and visualizing contingency tables.
* Explore differences - pivot tables and data visualizations including box-whisker plots.
* Share data - methods for exporting and sharing your datasets, summaries and
graphs.
Alongside the text, Have a Go exercises, Tips and Notes give readers practical experience and highlight important points, and helpful self-assessment exercises and summary tables can be found at the end of each chapter. Supplementary material can also be downloaded on the companion website.
Managing Data Using Excel is an essential book for all scientists and students who use data and are seeking to manage data more effectively. It is aimed at scientists at all levels but it is especially useful for university-level research, from undergraduates to postdoctoral researchers.
Readers will learn how to use Excel to:
* Build a dataset - how to handle variables and notes, rearrangements and edits to data.
* Check datasets - dealing with typographic errors, data validation and numerical
errors.
* Make sense of data - including datasets for regression and correlation; summarizing data with averages and variability; and visualizing data with graphs, pivot charts and sparklines.
* Explore regression data - finding, highlighting and visualizing correlations.
* Explore time-related data - using pivot tables, sparklines and line plots.
* Explore association data - creating and visualizing contingency tables.
* Explore differences - pivot tables and data visualizations including box-whisker plots.
* Share data - methods for exporting and sharing your datasets, summaries and
graphs.
Alongside the text, Have a Go exercises, Tips and Notes give readers practical experience and highlight important points, and helpful self-assessment exercises and summary tables can be found at the end of each chapter. Supplementary material can also be downloaded on the companion website.
Managing Data Using Excel is an essential book for all scientists and students who use data and are seeking to manage data more effectively. It is aimed at scientists at all levels but it is especially useful for university-level research, from undergraduates to postdoctoral researchers.
Reviews / Votes
Managing Data Using Excel ...... is a new book by Mark Gardener, published by Pelagic Publishing.*
It is subtitled "Organising, summarising and visualising scientific data". Clearly the book is aimed at scientists, particularly those dealing with the analysis of observational data, but is it of value to a wider audience? Having worked through the book I would say that it is definitely worthwhile for many other groups, including those in engineering and other branches of science and technology, and also those in commercial and marketing work dealing with the analysis of numerical data of any kind.
Aspects of the book that I found particularly useful were:
Detailed and clear descriptions of the use of pivot tables in the analysis and summary of numerical data of any kind (an area where I could certainly make more use of the features available in Excel)
Clearly laid out procedures for arranging, checking and exploring data.
Detailed procedures for display of data in a wide variety of graphs.
Detailed step-by step example spreadsheets available from the publisher's web-site.
This is certainly not a book "for dummies", and some may find the emphasis on scientific procedures off-putting, but for those willing to spend some time working through the examples I believe it will be of value to anyone who uses Excel to organise, summarise and visualise numerical data of any kind.
* Pelagic Publishing provided me with a free copy of the book for this review; I have no other connection with the publishers or the author. -- Doug Jenkins * Newton Excel Bach blog * Managing Data Using Excel: Organizing, Summarizing and Visualizing Scientific Data joins others in the 'Research Skills' series and is a top recommendation for any who would use their Excel spreadsheet skills to organize and share scientific data, standing out from the crowd of more general 'how to use Excel' handbooks to address the specific needs of the scientific community.
There are basics here, from how to build a dataset handling variables and notes to summarizing data using averages, creating visual displays with graphs and pivot charts, and using these tables to fine-tune results and displays that export well into datasets and summaries scientists can share.
Exercises are provided to reinforce concepts, while tips and notes compliment the educational process by pointing out common Excel challenges. Plenty of tables and charts pepper the discussions while an index makes it easy to use this is a reference for at-a-glance information.
Plenty of general Excel handbooks document how to create datasets and apply calculations, but the specific focus on scientific data manipulation provided here makes it a top recommendation over any general tutorial. -- Diane Donovan * Midwest Book Review *
More details
Series
Language
English
Place of publication
Exeter
United Kingdom
Target group
Professional and scholarly
Illustrations
202 Schaubilder, 30 s/w Tabellen
30 Tables, black and white; 202 Figures
Dimensions
Height: 234 mm
Width: 156 mm
Thickness: 18 mm
Weight
497 gr
ISBN-13
978-1-78427-007-0 (9781784270070)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Mark Gardener
Managing Data Using Excel
E-Book
03/2015
Pelagic Publishing
€39.99
Available for download
Mark Gardener
Managing Data Using Excel
Book
02/2015
Pelagic Publishing
€66.90
Shipment within 10-15 days
Person
Mark Gardener (www.gardenersown.co.uk) is an ecologist, lecturer, and writer working in the UK. His primary area of research was in pollination ecology and he has worked in the UK and around the word (principally Australia and the United States). Since his doctorate he has worked in many areas of ecology, often as a teacher and supervisor. He believes that ecological data, especially community data, is the most complicated and ill-behaved and is consequently the most fun to work with. He was introduced to R by a like-minded pedant whilst working in Australia during his doctorate. Learning R was not only fun but opened up a new avenue, making the study of community ecology a whole lot easier. He is currently self-employed and runs courses in ecology, data analysis, and R for a variety of organizations. Mark lives in rural Devon with his wife Christine, a biochemist who consequently has little need of statistics.
Content
1. Arranging your data
2. Managing your data: building your dataset
3. Managing your data: checking your dataset
4. Making sense of your data
5. Exploring regression data
6. Exploring time-related data
7. Exploring association data
8. Exploring differences data
9. Sharing your data
Appendices
Index
2. Managing your data: building your dataset
3. Managing your data: checking your dataset
4. Making sense of your data
5. Exploring regression data
6. Exploring time-related data
7. Exploring association data
8. Exploring differences data
9. Sharing your data
Appendices
Index