Data analysis with R : (Record no. 20218)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04013nam a2200229Ia 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | NULRC |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250520102954.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 250520s9999 xx 000 0 und d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781788393720 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | NULRC |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QA 276.45.R3 .F57 2018 |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Fischetti, Tony |
| Relator term | author |
| 245 #0 - TITLE STATEMENT | |
| Title | Data analysis with R : |
| Remainder of title | a comprehensive guide to manipulating, analyzing, and visualizing data in R / |
| Statement of responsibility, etc. | Tony Fischetti. |
| 250 ## - EDITION STATEMENT | |
| Edition statement | Second edition. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | Birmingham, UK : |
| Name of publisher, distributor, etc. | Packt Publishing, Limited, |
| Date of publication, distribution, etc. | c2018 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | vii, 553 pages : |
| Other physical details | illustrations ; |
| Dimensions | 23 cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Includes bibliographical references. |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: RefresheR; Navigating the basics; Arithmetic and assignment; Logicals and characters; Flow of control; Getting help in R; Vectors; Subsetting; Vectorized functions; Advanced subsetting; Recycling; Functions; Matrices; Loading data into R; Working with packages; Exercises; Summary; Chapter 2: The Shape of Data; Univariate data; Frequency distributions; Central tendency; Spread; Populations, samples, and estimation; Probability distributions; Visualization methods; Exercises; Summary. Chapter 3: Describing RelationshipsMultivariate data; Relationships between a categorical and continuous variable; Relationships between two categorical variables; The relationship between two continuous variables; Covariance; Correlation coefficients; Comparing multiple correlations; Visualization methods; Categorical and continuous variables; Two categorical variables; Two continuous variables; More than two continuous variables; Exercises; Summary; Chapter 4: Probability; Basic probability; A tale of two interpretations; Sampling from distributions; Parameters; The binomial distribution. The normal distributionThe three-sigma rule and using z-tables; Exercises; Summary; Chapter 5: Using Data To Reason About The World; Estimating means; The sampling distribution; Interval estimation; How did we get 1.96?; Smaller samples; Exercises; Summary; Chapter 6: Testing Hypotheses; The null hypothesis significance testing framework; One and two-tailed tests; Errors in NHST; A warning about significance; A warning about p-values; Testing the mean of one sample; Assumptions of the one sample t-test; Testing two means; Assumptions of the independent samples t-test. Testing more than two meansAssumptions of ANOVA; Testing independence of proportions; What if my assumptions are unfounded?; Exercises; Summary; Chapter 7: Bayesian Methods; The big idea behind Bayesian analysis; Choosing a prior; Who cares about coin flips; Enter MCMC -- stage left; Using JAGS and runjags; Fitting distributions the Bayesian way; The Bayesian independent samples t-test; Exercises; Summary; Chapter 8: The Bootstrap; What's ... uhhh ... the deal with the bootstrap?; Performing the bootstrap in R (more elegantly); Confidence intervals; A one-sample test of means. Bootstrapping statistics other than the meanBusting bootstrap myths; What have we left out?; Exercises; Summary; Chapter 9: Predicting Continuous Variables; Linear models; Simple linear regression; Simple linear regression with a binary predictor; A word of warning; Multiple regression; Regression with a non-binary predictor; Kitchen sink regression; The bias-variance trade-off; Cross-validation; Striking a balance; Linear regression diagnostics; Second Anscombe relationship; Third Anscombe relationship; Fourth Anscombe relationship; Advanced topics; Exercises; Summary. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | R has spread deep into the private sector and can be found in the production pipelines at some of the most advanced and successful enterprises. Starting with the basics of R and statistical reasoning, this book dives into advanced predictive analytics, showing how to apply those techniques to real-world data though with real-world examples. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | R (COMPUTER PROGRAM LANGUAGE) |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Library of Congress Classification |
| Koha item type | Books |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Total checkouts | Full call number | Barcode | Date last seen | Copy number | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Library of Congress Classification | Machine Learning | LRC - Main | National University - Manila | General Circulation | 09/08/2020 | Purchased - Amazon | 39.99 | GC QA 276.45.R3 .F57 2018 | NULIB000017977 | 05/20/2025 | c.1 | 05/20/2025 | Books |