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210123 ||| eng |
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|a 9781635267181
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|a 9781635267204
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|a 1635267188
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4 |
|a QA276.45.J56
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| 100 |
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|a Figard, Steve
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| 245 |
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|a Introduction to biostatistics with JMP
|c Steve Figard
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| 260 |
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|a Cary, NC
|b SAS Institute
|c 2019
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| 300 |
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|a 1 online resource
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|a There Are Error Bars, and Then There Are Error BarsSo, You Want to Put Error Bars on Your JMP Graphs ... ; Chapter 6: Null Hypothesis Significance Testing; Introduction; Biological Versus Statistical Ho; NHST Rationale; Error Types; A Case Study in JMP; Chapter 7: Tests on Frequencies: Analyzing Rates and Proportions; Introduction; Y.O.D.A. Assessment; One-way Chi-Square Tests and Mendel's Peas; Two-way Chi-Square Tests and Piscine Brain Worms; Chapter 8: Tests on Frequencies: Odds Ratios and Relative Risk; Introduction; Experimental Design and Data Collection; Relative Risk; Odds Ratios
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|a It Is Difficult to Make Predictions, Especially About the FutureChapter 12: Tests of Association: Correlation; Introduction; What Is Correlation?; How Does It Work?; What Can't Correlation Do?; How to Calculate Correlation Coefficients: An Eyepopping Example; Chapter 13: Modeling Trends: Multiple Regression; Introduction; What Is Multiple Regression?; The Fit Model Platform Is Your Friend!; Let's Throw All of Them in ... ; Stepwise; Chapter 14: Modeling Trends: Other Regression Models; Introduction; Modeling Nominal Responses; It's Not Linear! Now What?; Predictions
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|a Chapter 9: Tests of Differences Between Two GroupsIntroduction; Comparing Two Unrelated Samples and Bone Density; Comparing Two Related Samples and Secondhand Smoke; Chapter 10: Tests of Differences Between More Than Two Groups; Introduction; Comparing Unrelated Data; Comparing Related Data; Chapter 11: Tests of Association: Regression; Introduction; What Is Bivariate Linear Regression?; What Is Regression?; What Does Linear Regression Tell Us?; What Are the Assumptions of Linear Regression?; Is Your Weight Related to Your Fat?; How Do You Identify Independent and Dependent Variables?
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|a Intro; Contents; About This Book; What Does This Book Cover?; Is This Book for You?; What Should You Know about the Examples?; We Want to Hear from You; About The Author; Chapter 1: Some JMP Basics; Introduction; JMP Help; Manual Data Entry; Opening Excel Files; Column Information -- Value Ordering; Formulas; "Platforms"; The Little Red Triangle is Your Friend!; Row States -- Color and Markers; Row States -- Hiding and Excluding; Saving Scripts; Saving Outputs -- Journals & RTF Files; Graph Builder; Chapter 2: Thinking Statistically; Thinking Like a Statistician; Summary
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|a Includes bibliographical references
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|a Chapter 3: Statistical Topics in Experimental DesignIntroduction; Sample Size and Power; Replication and Pseudoreplication; Randomization and Preventing Bias; Variation and Variables; Chapter 4: Describing Populations; Introduction; Population Description; The Most Common Distribution -- Normal or Gaussian; Two Other Biologically Relevant Distributions; The JMP Distribution Platform; An Example: Big Class.jmp; Parametric versus Nonparametric and "Normal Enough"; Chapter 5: Inferring and Estimating; Introduction; Inferential Estimation; Confidence Intervals
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| 653 |
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|a Biometry / Statistical methods
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| 653 |
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|a Medicine / Research / Statistical methods
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| 653 |
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|a JMP (Computer file) / fast
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| 653 |
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|a Medicine / Research / Statistical methods / fast
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| 653 |
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|a Biometry / Statistical methods / fast
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| 653 |
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|a JMP (Computer file) / http://id.loc.gov/authorities/names/n97119732
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| 653 |
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|a Biométrie / Méthodes statistiques
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| 653 |
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|a Médecine / Recherche / Méthodes statistiques
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| 041 |
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|a eng
|2 ISO 639-2
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| 989 |
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|b OREILLY
|a O'Reilly
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| 776 |
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|z 9781629606330
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| 776 |
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|z 1629606332
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| 776 |
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|z 1635267188
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| 776 |
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|z 9781635267181
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| 856 |
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|u https://learning.oreilly.com/library/view/~/9781635267181/?ar
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 570.15195
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| 520 |
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|a 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 an
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