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This book offers researchers and practitioners a concise and accessible guide to the essential concepts in statistics, emphasizing their proper application. It encourages readers to delve deeper into the fascinating field of statistics, a branch of mathematics that enhances our understanding of the world around us. Designed to provide enough material for a short introductory course, Statistics for Scientists caters to students at all levels. It emphasizes real-world applications, providing scientists with the tools they need to conduct more reliable and valid studies, ultimately contributing to the advancement of scientific knowledge. Learn to interpret statistical results accurately and draw meaningful conclusions from your data, significantly contributing to the advancement of scientific knowledge.
Structured to deliver a clear overview of statistics and data analysis for scientific research, the book begins with fundamental concepts, including random variables, outcome spaces, and the distinction between descriptive and inferential statistics. It then explores data types, measures of central tendency, dispersion, and position. The discussion continues with an examination of outliers and various methods for identifying them. As the chapters progress, more complex topics such as distributions, hypothesis testing, and regression analysis are introduced in a step-by-step manner. This structure makes the book suitable for readers ranging from beginners to those seeking a quick refresher.
The author has selected key concepts that anyone interested in using statistics should be familiar with. Some topics, such as hypothesis testing, are covered briefly; a more comprehensive treatment would require a stronger background in statistics and mathematics (such as calculus). With pedagogical elements that include text boxes with Definitions, Examples, and Warnings, this book introduces the necessary concepts of statistics for scientists described in a short and concise way, enriched with tips and rigorous explanations. This book is an invaluable resource for scientists seeking to improve their data analysis skills and contribute to the growing body of scientific knowledge through rigorous and reliable research.
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I lager, skickas inom 4 till 5 vardagar
Klaus Solberg Søilen
Paul Wilkins, Pete Sanders
Matthew Loveless
Graham R. Gibbs
David Coghlan
Felix C. ) Tropf, Melinda C. Mills, Nicola Barban
Craig K. Enders
Serena Quarta
Bernard Grofman
David Doane, Lori Seward
Gouri K. Bhattacharyya, Richard A. Johnson
Audrey R. Giles
Maria Elena Torre, Michelle Fine
D. V. Lindley, W. F. Scott
Douglas Lind, Samuel Wathen, William Marchal
Peter A. Rogerson
Roehl Sybing
Ivory A. Toldson
Brody Heritage, Kellie Bennett, Peter Allen
Norean Sharpe, Paul Velleman, Richard De Veaux
Deborah Mikyo Oh
Ailsa Roell, Marco Pagano, Thierry Foucault
Sarah Easter Collins
Frida Skybäck
Liz Moore
Colleen Hoover
Kristin Fägerskjöld
Armando Lucas Correa
Sharon Bolton
Ruth Lillegraven
Santa Montefiore
Kelly Rimmer
Martha Hall Kelly
Svenja O'Donnell
Nathan Harris
Holly Jackson
Louise Boije af Gennäs
Tina Norin
Kristin Fägerskjöld
Pernilla Lindroos
Anna Lönnqvist
Jessie Burton
Malin Nordström
Marc Levy
Emma Donoghue
Snezana Lindskog, Andie Lindskog
Tony Samuelsson
Andrev Walden
Tina Harnesk
Kathrine Nedrejord
Anthony Doerr
Marieke Lucas Rijneveld
Lauren Groff
Claire Messud
Claire Lynch
Sebastian Barry
Ray Celestin
Simon Stranger
Alice Munro
Linda Boström Knausgård
Marit Kapla
Ulf Stark
Sarah Easter Collins
Liz Moore
Ursula Scavenius
Colleen Hoover
Michel Jean
