The Resource Reasoning with data : an introduction to traditional and Bayesian statistics using R, Jeffrey M. Stanton, (electronic book)
Reasoning with data : an introduction to traditional and Bayesian statistics using R, Jeffrey M. Stanton, (electronic book)
Resource Information
The item Reasoning with data : an introduction to traditional and Bayesian statistics using R, Jeffrey M. Stanton, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.This item is available to borrow from 1 library branch.
Resource Information
The item Reasoning with data : an introduction to traditional and Bayesian statistics using R, Jeffrey M. Stanton, (electronic book) represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Liverpool.
This item is available to borrow from 1 library branch.
 Summary
 Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides stepbystep guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the opensource R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using realdata examples. The companion website provides annotated R code for the book's examples, inclass exercises, supplemental reading lists, and links to online videos, interactive materials, and other resources.Pedagogical Features:*Playful, conversational style and gradual approach; suitable for students without strong math backgrounds.*Endofchapter exercises based on real data supplied in the free R package.*Technical Explanation and Equation/Output boxes.*Appendices on how to install R and work with the sample datasets
 Language
 eng
 Extent
 325 pages
 Contents

 <p>Introduction<br>Getting Started<br>1. Statistical Vocabulary<br>Descriptive Statistics<br>Measures of Central Tendency<br>Measures of Dispersion<br>Distributions and Their Shapes<br>Conclusion<br>Exercises<br>2. Reasoning with Probability<br>Outcome Tables<br>Contingency Tables<br>Conclusion<br>Exercises<br>3. Probabilities in the Long Run<br>Sampling<br>Repetitious Sampling with R<br>Using Sampling Distributions and Quantiles to Think about Probabilities<br>Conclusion<br>Exercises<br>4. Introducing the Logic of Inference Using Confidence Intervals<br>Exploring the Variability of Sample Means with Repetitious Sampling<br>Our First Inferential Test: The Confidence Interval<br>Conclusion<br>Exercises<br>5. Bayesian and Traditional Hypothesis Testing<br>The Null Hypothesis Significance Test<br>Replication and the NHST<br>Conclusion<br>Exercises<br>6. Comparing Groups and Analyzing Experiments<br>Frequentist Approach to ANOVA<br>Bayesian Approach to ANOVA<br>Finding an Effect<br>Conclusion<br>Exercises<br>7. Associations between Variables<br>Inferential Reasoning about Correlation<br>Null Hypothesis Testing on the Correlation<br>Bayesian Tests on the Correlation Coefficient<br>Categorical Associations<br>Exploring the ChiSquare Distribution with a Simulation<br>The ChiSquare Test with Real Data<br>Bayesian Approach to ChiSquare Test<br>Conclusion<br>Exercises<br>8. Linear Multiple Regression<br>Bayesian Approach to Linear Regression<br>A Linear Regression Model with Real Data<br>Conclusion<br>Exercises<br>9. Interactions in ANOVA and Regression<br>Interactions in ANOVA<br>Interactions in Multiple Regression<br>Bayesian Analysis of Regression Interactions<br>Conclusion<br>Exercises<br>10. Logistic Regression<br>A Logistic Regression Model with Real Data<br>Bayesian Estimation of Logistic Regression<br>Conclusion<br>Exercises<br>11. Analyzing Change over Time<br>Repeated Measures Analysis<br>TimeSeries Analysis<br>Exploring a Time Series with Real Data<br>Finding Change Points in Time Series<br>Probabilities in ChangePoint Analysis<br>Conclusion<br>Exercises<br>12. Dealing with Too Many Variables<br>Internal Consistency Reliability<br>Rotation<br>Conclusion<br>Exercises<br>13. All Together Now<br>The Big Picture<br>Appendix A. Getting Started with R<br>Running R and Typing Commands<br>Installing Packages<br>Quitting, Saving, and Restoring<br>Conclusion<br>Appendix B. Working with Data Sets in R<br>Data Frames in R<br>Reading Data Frames from External Files<br>Appendix C. Using dplyr with Data Frames<br>References<br>Index<br></p>
 Isbn
 9781462530298
 Label
 Reasoning with data : an introduction to traditional and Bayesian statistics using R
 Title
 Reasoning with data
 Title remainder
 an introduction to traditional and Bayesian statistics using R
 Statement of responsibility
 Jeffrey M. Stanton
 Language
 eng
 Summary
 Engaging and accessible, this book teaches readers how to use inferential statistical thinking to check their assumptions, assess evidence about their beliefs, and avoid overinterpreting results that may look more promising than they really are. It provides stepbystep guidance for using both classical (frequentist) and Bayesian approaches to inference. Statistical techniques covered side by side from both frequentist and Bayesian approaches include hypothesis testing, replication, analysis of variance, calculation of effect sizes, regression, time series analysis, and more. Students also get a complete introduction to the opensource R programming language and its key packages. Throughout the text, simple commands in R demonstrate essential data analysis skills using realdata examples. The companion website provides annotated R code for the book's examples, inclass exercises, supplemental reading lists, and links to online videos, interactive materials, and other resources.Pedagogical Features:*Playful, conversational style and gradual approach; suitable for students without strong math backgrounds.*Endofchapter exercises based on real data supplied in the free R package.*Technical Explanation and Equation/Output boxes.*Appendices on how to install R and work with the sample datasets
 Cataloging source

 StDuBDS
 StDuBDS
 http://library.link/vocab/creatorDate
 1961
 http://library.link/vocab/creatorName
 Stanton, Jeffrey M.
 Dewey number
 519.5028553
 Index
 no index present
 LC call number
 QA279.5
 Literary form
 non fiction
 http://library.link/vocab/subjectName

 Bayesian statistical decision theory
 Mathematical statistics
 Bayesian statistical decision theory
 Mathematical statistics
 R (Computer program language)
 Target audience
 specialized
 Label
 Reasoning with data : an introduction to traditional and Bayesian statistics using R, Jeffrey M. Stanton, (electronic book)
 Carrier category
 online resource
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type MARC source
 rdacontent
 Contents
 <p>Introduction<br>Getting Started<br>1. Statistical Vocabulary<br>Descriptive Statistics<br>Measures of Central Tendency<br>Measures of Dispersion<br>Distributions and Their Shapes<br>Conclusion<br>Exercises<br>2. Reasoning with Probability<br>Outcome Tables<br>Contingency Tables<br>Conclusion<br>Exercises<br>3. Probabilities in the Long Run<br>Sampling<br>Repetitious Sampling with R<br>Using Sampling Distributions and Quantiles to Think about Probabilities<br>Conclusion<br>Exercises<br>4. Introducing the Logic of Inference Using Confidence Intervals<br>Exploring the Variability of Sample Means with Repetitious Sampling<br>Our First Inferential Test: The Confidence Interval<br>Conclusion<br>Exercises<br>5. Bayesian and Traditional Hypothesis Testing<br>The Null Hypothesis Significance Test<br>Replication and the NHST<br>Conclusion<br>Exercises<br>6. Comparing Groups and Analyzing Experiments<br>Frequentist Approach to ANOVA<br>Bayesian Approach to ANOVA<br>Finding an Effect<br>Conclusion<br>Exercises<br>7. Associations between Variables<br>Inferential Reasoning about Correlation<br>Null Hypothesis Testing on the Correlation<br>Bayesian Tests on the Correlation Coefficient<br>Categorical Associations<br>Exploring the ChiSquare Distribution with a Simulation<br>The ChiSquare Test with Real Data<br>Bayesian Approach to ChiSquare Test<br>Conclusion<br>Exercises<br>8. Linear Multiple Regression<br>Bayesian Approach to Linear Regression<br>A Linear Regression Model with Real Data<br>Conclusion<br>Exercises<br>9. Interactions in ANOVA and Regression<br>Interactions in ANOVA<br>Interactions in Multiple Regression<br>Bayesian Analysis of Regression Interactions<br>Conclusion<br>Exercises<br>10. Logistic Regression<br>A Logistic Regression Model with Real Data<br>Bayesian Estimation of Logistic Regression<br>Conclusion<br>Exercises<br>11. Analyzing Change over Time<br>Repeated Measures Analysis<br>TimeSeries Analysis<br>Exploring a Time Series with Real Data<br>Finding Change Points in Time Series<br>Probabilities in ChangePoint Analysis<br>Conclusion<br>Exercises<br>12. Dealing with Too Many Variables<br>Internal Consistency Reliability<br>Rotation<br>Conclusion<br>Exercises<br>13. All Together Now<br>The Big Picture<br>Appendix A. Getting Started with R<br>Running R and Typing Commands<br>Installing Packages<br>Quitting, Saving, and Restoring<br>Conclusion<br>Appendix B. Working with Data Sets in R<br>Data Frames in R<br>Reading Data Frames from External Files<br>Appendix C. Using dplyr with Data Frames<br>References<br>Index<br></p>
 Control code
 AH32199632
 Extent
 325 pages
 Form of item
 electronic
 Governing access note
 After 5 minutes Preview, click on 2Request Access3, fill in a form with your details. If triggered, the book will be loaned and tied to the one user for 1 week, during which time users can read or download as they choose. 4th user request triggers autopurchase
 Isbn
 9781462530298
 Media category
 computer
 Media MARC source
 rdamedia
 Specific material designation
 remote
 Label
 Reasoning with data : an introduction to traditional and Bayesian statistics using R, Jeffrey M. Stanton, (electronic book)
 Carrier category
 online resource
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type MARC source
 rdacontent
 Contents
 <p>Introduction<br>Getting Started<br>1. Statistical Vocabulary<br>Descriptive Statistics<br>Measures of Central Tendency<br>Measures of Dispersion<br>Distributions and Their Shapes<br>Conclusion<br>Exercises<br>2. Reasoning with Probability<br>Outcome Tables<br>Contingency Tables<br>Conclusion<br>Exercises<br>3. Probabilities in the Long Run<br>Sampling<br>Repetitious Sampling with R<br>Using Sampling Distributions and Quantiles to Think about Probabilities<br>Conclusion<br>Exercises<br>4. Introducing the Logic of Inference Using Confidence Intervals<br>Exploring the Variability of Sample Means with Repetitious Sampling<br>Our First Inferential Test: The Confidence Interval<br>Conclusion<br>Exercises<br>5. Bayesian and Traditional Hypothesis Testing<br>The Null Hypothesis Significance Test<br>Replication and the NHST<br>Conclusion<br>Exercises<br>6. Comparing Groups and Analyzing Experiments<br>Frequentist Approach to ANOVA<br>Bayesian Approach to ANOVA<br>Finding an Effect<br>Conclusion<br>Exercises<br>7. Associations between Variables<br>Inferential Reasoning about Correlation<br>Null Hypothesis Testing on the Correlation<br>Bayesian Tests on the Correlation Coefficient<br>Categorical Associations<br>Exploring the ChiSquare Distribution with a Simulation<br>The ChiSquare Test with Real Data<br>Bayesian Approach to ChiSquare Test<br>Conclusion<br>Exercises<br>8. Linear Multiple Regression<br>Bayesian Approach to Linear Regression<br>A Linear Regression Model with Real Data<br>Conclusion<br>Exercises<br>9. Interactions in ANOVA and Regression<br>Interactions in ANOVA<br>Interactions in Multiple Regression<br>Bayesian Analysis of Regression Interactions<br>Conclusion<br>Exercises<br>10. Logistic Regression<br>A Logistic Regression Model with Real Data<br>Bayesian Estimation of Logistic Regression<br>Conclusion<br>Exercises<br>11. Analyzing Change over Time<br>Repeated Measures Analysis<br>TimeSeries Analysis<br>Exploring a Time Series with Real Data<br>Finding Change Points in Time Series<br>Probabilities in ChangePoint Analysis<br>Conclusion<br>Exercises<br>12. Dealing with Too Many Variables<br>Internal Consistency Reliability<br>Rotation<br>Conclusion<br>Exercises<br>13. All Together Now<br>The Big Picture<br>Appendix A. Getting Started with R<br>Running R and Typing Commands<br>Installing Packages<br>Quitting, Saving, and Restoring<br>Conclusion<br>Appendix B. Working with Data Sets in R<br>Data Frames in R<br>Reading Data Frames from External Files<br>Appendix C. Using dplyr with Data Frames<br>References<br>Index<br></p>
 Control code
 AH32199632
 Extent
 325 pages
 Form of item
 electronic
 Governing access note
 After 5 minutes Preview, click on 2Request Access3, fill in a form with your details. If triggered, the book will be loaned and tied to the one user for 1 week, during which time users can read or download as they choose. 4th user request triggers autopurchase
 Isbn
 9781462530298
 Media category
 computer
 Media MARC source
 rdamedia
 Specific material designation
 remote
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