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Understanding Statistics and Experimental Design

This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and...

Повний опис

Збережено в:
Автори: Herzog, Michael H., Francis, Gregory, Clarke, Aaron
Формат: Online
Мова:Англійська
Опубліковано: Springer Nature 2021
Предмети:
Medicine
Molecular biology
Biostatistics
Science education
Statistics
Experiential research
Behavioral sciences
Textbook
thema EDItEUR::J Society and Social Sciences::JM Psychology::JMB Psychological methodology
thema EDItEUR::J Society and Social Sciences::JN Education::JNU Teaching of a specific subject
thema EDItEUR::M Medicine and Nursing::MB Medicine: general issues::MBG Medical equipment and techniques::MBGR Medical research
thema EDItEUR::P Mathematics and Science::PB Mathematics::PBT Probability and statistics
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSV Zoology and animal sciences::PSVP Ethology and animal behaviour
Онлайн доступ:1007132
Теги: Додати тег
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Резюме:This open access textbook provides the background needed to correctly use, interpret and understand statistics and statistical data in diverse settings. Part I makes key concepts in statistics readily clear. Parts I and II give an overview of the most common tests (t-test, ANOVA, correlations) and work out their statistical principles. Part III provides insight into meta-statistics (statistics of statistics) and demonstrates why experiments often do not replicate. Finally, the textbook shows how complex statistics can be avoided by using clever experimental design. Both non-scientists and students in Biology, Biomedicine and Engineering will benefit from the book by learning the statistical basis of scientific claims and by discovering ways to evaluate the quality of scientific reports in academic journals and news outlets.

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