Biostatistics by Example Using SAS Studio
(eBook)

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SAS Institute, 2016.
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Format
eBook
Language
English
ISBN
9781629604930

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Citations

APA Citation, 7th Edition (style guide)

Ron Cody., & Ron Cody|AUTHOR. (2016). Biostatistics by Example Using SAS Studio . SAS Institute.

Chicago / Turabian - Author Date Citation, 17th Edition (style guide)

Ron Cody and Ron Cody|AUTHOR. 2016. Biostatistics By Example Using SAS Studio. SAS Institute.

Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)

Ron Cody and Ron Cody|AUTHOR. Biostatistics By Example Using SAS Studio SAS Institute, 2016.

MLA Citation, 9th Edition (style guide)

Ron Cody, and Ron Cody|AUTHOR. Biostatistics By Example Using SAS Studio SAS Institute, 2016.

Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.

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Grouped Work IDc97d7fb6-4ce2-f622-276f-fe17e393b32a-eng
Full titlebiostatistics by example using sas studio
Authorcody ron
Grouping Categorybook
Last Update2022-10-18 21:40:45PM
Last Indexed2024-04-20 02:55:20AM

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    [synopsis] => Learn how to solve basic statistical problems with Ron Cody's easy-to-follow style using the point-and-click SAS Studio tasks. 
Aimed specifically at the health sciences, Biostatistics by Example Using SAS Studio provides an introduction to SAS Studio tasks. The book includes many biological and health-related problem sets and is fully compatible with SAS University Edition. 
After reading this book you will be able to understand temporary and permanent SAS data sets, and you will learn how to create them from various data sources. You will also be able to use SAS Studio statistics tasks to generate descriptive statistics for continuous and categorical data. 
The inferential statistics portion of the book covers the following topics: 
-Paired and unpaired t tests. 
-One-way analysis of variance.
-N-way ANOVA.
-Correlation. 
-Simple and multiple regression. 
-Logistic regression. 
-Categorical data analysis. 
-Power and sample size calculations. 
Besides describing each of these statistical tests, the book also discusses the assumptions that need to be met before running and interpreting these tests. For two-sample tests and N-way tests, nonparametric tests are also described. 
This book leads you step-by-step through each of the statistical tests with numerous screen shots, and you will see how to read and interpret all of the output generated by these tests. 
Experience with some basic statistical tests used to analyze medical data or classroom experience in biostatistics or statistics is required. Although the examples are related to the medical and biology fields, researchers in other fields such as psychology or education will find this book helpful. No programming experience is required. 
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