Introduction to Biostatistics with JMP
- 3h 37m
- Steve Figard
- SAS Institute
- 2019
Explore biostatistics using JMP in this refreshing introduction
Presented in an easy-to-understand way, Introduction to Biostatistics with JMP introduces undergraduate students in the biological sciences to the most commonly used (and misused) statistical methods that they will need to analyze their experimental data using JMP. It covers many of the basic topics in statistics using biological examples for exercises so that the student biologists can see the relevance to future work in the problems addressed.
The book starts by teaching students how to become confident in executing the right analysis by thinking like a statistician then moves into the application of specific tests. Using the powerful capabilities of JMP, the book addresses problems requiring analysis by chi-square tests, t tests, ANOVA analysis, various regression models, DOE, and survival analysis. Topics of particular interest to the biological or health science field include odds ratios, relative risk, and survival analysis.
The author uses an engaging, conversational tone to explain concepts and keep readers interested in learning more. The book aims to create bioscientists who can competently incorporate statistics into their investigative toolkits to solve biological research questions as they arise.
About the Author
The author walks the audience through a brief introduction to JMP and basic statistical theory/application, eventually leading them to more advanced and commonly used applications such as regression and time series modeling." -- Deanna Schreiber-Gregory, Independent Consultant - Statistical Theory and Data Management "Juxdapoze"
In this Book
-
About This Book
-
Some JMP Basics
-
Thinking Statistically
-
Statistical Topics in Experimental Design
-
Describing Populations
-
Inferring and Estimating
-
Null Hypothesis Significance Testing
-
Tests on Frequencies—Analyzing Rates and Proportions
-
Tests on Frequencies—Odds Ratios and Relative Risk
-
Tests of Differences between Two Groups
-
Tests of Differences between More than Two Groups
-
Tests of Association—Regression
-
Tests of Association—Correlation
-
Modeling Trends—Multiple Regression
-
Modeling Trends—Other Regression Models
-
Modeling Trends—Generalized Linear Models
-
Design of Experiments (DOE)
-
Survival Analysis
-
Hindrances to Data Analysis
