Data Analysis with R (Record no. 2343)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 05422nam a22001817a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20240723123350.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240723b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781788393720 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 001.422 |
| Item number | FIS |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Fischetti, Anthony |
| 245 ## - 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. | Anthony Fischetti |
| 250 ## - EDITION STATEMENT | |
| Edition statement | Second Edition |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication, distribution, etc. | UK |
| Name of publisher, distributor, etc. | Packt> |
| Date of publication, distribution, etc. | 2018 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Page number | 553 |
| 505 ## - FORMATTED CONTENTS NOTE | |
| Title | 1. RefresheR<br/>RefresheR<br/>Navigating the basics<br/>Getting help in R<br/>Vectors<br/>Functions<br/>Matrices<br/>Loading data into R<br/>Working with packages<br/>Exercises<br/>Summary<br/>2. The Shape of Data<br/>The Shape of Data<br/>Univariate data<br/>Frequency distributions<br/>Central tendency<br/>Spread<br/>Populations, samples, and estimation<br/>Probability distributions<br/>Visualization methods<br/>Exercises<br/>Summary<br/>3. Describing Relationships<br/>Describing Relationships<br/>Multivariate data<br/>Relationships between a categorical and continuous variable<br/>Relationships between two categorical variables<br/>The relationship between two continuous variables<br/>Visualization methods<br/>Exercises<br/>Summary<br/>4. Probability<br/>Probability<br/>Basic probability<br/>A tale of two interpretations<br/>Sampling from distributions<br/>The normal distribution<br/>Exercises<br/>Summary<br/>5. Using Data To Reason About The World<br/>Using Data To Reason About The World<br/>Estimating means<br/>The sampling distribution<br/>Interval estimation<br/>Smaller samples<br/>Exercises<br/>Summary<br/>6. Testing Hypotheses<br/>Testing Hypotheses<br/>The null hypothesis significance testing framework<br/>Testing the mean of one sample<br/>Testing two means<br/>Testing more than two means<br/>Testing independence of proportions<br/>What if my assumptions are unfounded?<br/>Exercises<br/>Summary<br/>7. Bayesian Methods<br/>Bayesian Methods<br/>The big idea behind Bayesian analysis<br/>Choosing a prior<br/>Who cares about coin flips<br/>Enter MCMC – stage left<br/>Using JAGS and runjags<br/>Fitting distributions the Bayesian way<br/>The Bayesian independent samples t-test<br/>Exercises<br/>Summary<br/>8. The Bootstrap<br/>The Bootstrap<br/>What's... uhhh... the deal with the bootstrap?<br/>Performing the bootstrap in R (more elegantly)<br/>Confidence intervals<br/>A one-sample test of means<br/>Bootstrapping statistics other than the mean<br/>Busting bootstrap myths<br/>Exercises<br/>Summary<br/>9. Predicting Continuous Variables<br/>Predicting Continuous Variables<br/>Linear models<br/>Simple linear regression<br/>Simple linear regression with a binary predictor<br/>Multiple regression<br/>Regression with a non-binary predictor<br/>Kitchen sink regression<br/>The bias-variance trade-off<br/>Linear regression diagnostics<br/>Advanced topics<br/>Exercises<br/>Summary<br/>10. Predicting Categorical Variables<br/>Predicting Categorical Variables<br/>k-Nearest neighbors<br/>Logistic regression<br/>Decision trees<br/>Random forests<br/>Choosing a classifier<br/>Exercises<br/>Summary<br/>11. Predicting Changes with Time<br/>Predicting Changes with Time<br/>What is a time series?<br/>What is forecasting?<br/>Creating and plotting time series<br/>Components of time series<br/>Time series decomposition<br/>White noise<br/>Autocorrelation<br/>Smoothing<br/>ETS and the state space model<br/>Interventions for improvement<br/>What we didn't cover<br/>Citations for the climate change data<br/>Exercises<br/>Summary<br/>12. Sources of Data<br/>Sources of Data<br/>Relational databases<br/>Using JSON<br/>XML<br/>Other data formats<br/>Online repositories<br/>Exercises<br/>Summary<br/>13. Dealing with Missing Data<br/>Dealing with Missing Data<br/>Analysis with missing data<br/>Visualizing missing data<br/>Types of missing data<br/>Unsophisticated methods for dealing with missing data<br/>So how does mice come up with the imputed values?<br/>Exercises<br/>Summary<br/>14. Dealing with Messy Data<br/>Dealing with Messy Data<br/>Checking unsanitized data<br/>Regular expressions<br/>Other tools for messy data<br/>Exercises<br/>Summary<br/>15. Dealing with Large Data<br/>Dealing with Large Data<br/>Wait to optimize<br/>Using a bigger and faster machine<br/>Be smart about your code<br/>Using optimized packages<br/>Using another R implementation<br/>Using parallelization<br/>Using Rcpp<br/>Being smarter about your code<br/>Exercises<br/>Summary<br/>16. Working with Popular R Packages<br/>Working with Popular R Packages<br/>The data.table package<br/>Using dplyr and tidyr to manipulate data<br/>Functional programming as a main tidyverse principle<br/>Reshaping data with tidyr<br/>Exercises<br/>Summary<br/>17. Reproducibility and Best Practices |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Frequently the tool of choice for academics, 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. The power and domain-specificity of R allows the user to express complex analytics easily, quickly, and succinctly. 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. Packed with engaging problems and exercises, this book begins with a review of R and its syntax with packages like Rcpp, ggplot2, and dplyr. From there, get to grips with the fundamentals of applied statistics and build on this knowledge to perform sophisticated and powerful analytics. Solve the difficulties relating to performing data analysis in practice and find solutions to working with messy data, large data, communicating results, and facilitating reproducibility. This book is engineered to be an invaluable resource through many stages of anyone’s career as a data analyst. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Books |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| -- | 6852 |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| -- | 6853 |
| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
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| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
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| 952 ## - LOCATION AND ITEM INFORMATION (KOHA) | |
| -- | 6856 |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Inventory number | Total Checkouts | Full call number | Barcode | Date last seen | Cost, replacement price | Price effective from | Currency | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Non-fiction | IIITDM Kurnool | IIITDM Kurnool | COMPUTER SCIENCE ENGINEERING | 23.07.2024 | Technical Bureau India | 3299.00 | TB889 DT 6-7-2024 | 001.422 FIS | 0005839 | 23.07.2024 | 3299.00 | 23.07.2024 | INR | Books | |||||
| Dewey Decimal Classification | Non-fiction | IIITDM Kurnool | IIITDM Kurnool | COMPUTER SCIENCE ENGINEERING | 23.07.2024 | Technical Bureau India | 3299.00 | TB889 DT 6-7-2024 | 001.422 FIS | 0005840 | 23.07.2024 | 3299.00 | 23.07.2024 | INR | Books | |||||
| Dewey Decimal Classification | Non-fiction | IIITDM Kurnool | IIITDM Kurnool | COMPUTER SCIENCE ENGINEERING | 23.07.2024 | Technical Bureau India | 3299.00 | TB889 DT 6-7-2024 | 001.422 FIS | 0005841 | 23.07.2024 | 3299.00 | 23.07.2024 | INR | Books | |||||
| Dewey Decimal Classification | Non-fiction | IIITDM Kurnool | IIITDM Kurnool | COMPUTER SCIENCE ENGINEERING | 23.07.2024 | Technical Bureau India | 3299.00 | TB889 DT 6-7-2024 | 001.422 FIS | 0005842 | 23.07.2024 | 3299.00 | 23.07.2024 | INR | Books | |||||
| Dewey Decimal Classification | Not For Loan | Non-fiction | IIITDM Kurnool | IIITDM Kurnool | Reference | 23.07.2024 | Technical Bureau India | 3299.00 | TB889 DT 6-7-2024 | 001.422 FIS | 0005843 | 23.07.2024 | 3299.00 | 23.07.2024 | INR | Reference |