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Beginning R : an introduction to statistical programming

Author: Joshua F Wiley; Larry A Pace
Publisher: [Berkeley, CA] : Apress, [2015] ©2015
Series: Expert's voice in programming.
Edition/Format:   eBook : Document : English : Second editionView all editions and formats
Summary:
Beginning R, Second Edition is a hands-on book showing how to use the R language, write and save R scripts, read in data files, and write custom statistical functions as well as use built in functions. This book shows the use of R in specific cases such as one-way ANOVA analysis, linear and logistic regression, data visualization, parallel processing, bootstrapping, and more. It takes a hands-on, example-based  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Wiley, Joshua F.
Beginning R.
[Berkeley, CA] : Apress, [2015]
(OCoLC)921191221
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Joshua F Wiley; Larry A Pace
ISBN: 9781484203736 1484203739
OCLC Number: 926914972
Notes: Includes index.
Description: 1 online resource.
Contents: Machine generated contents note: 1.1. What is R, Anyway? --
1.2. First R Session --
1.3. Your Second R Session --
1.3.1. Working with Indexes --
1.3.2. Representing Missing Data in R --
1.3.3. Vectors and Vectorization in R --
1.3.4. Brief Introduction to Matrices --
1.3.5. More on Lists --
1.3.6. Quick Introduction to Data Frames --
2.1. Working with Dates and Times --
2.2. Working with Strings --
2.3. Working with Data Frames in the Real World --
2.3.1. Finding and Subsetting Data --
2.4. Manipulating Data Structures --
2.5. Hard Work of Working with Larger Datasets --
3.1. R Input --
3.1.1. R Editor --
3.1.2. R Data Editor --
3.1.3. Other Ways to Get Data Into R --
3.1.4. Reading Data from a File --
3.1.5. Getting Data from the Web --
3.2. R Output --
3.2.1. Saving Output to a File --
4.1. Using Logic --
4.2. Flow Control --
4.2.1. Explicit Looping --
4.2.2. Implicit Looping --
4.3. If, If-Else, and ifelse() Statements --
5.1. Scoping Rules --
5.2. Reserved Names and Syntactically Correct Names --
5.3. Functions and Arguments --
5.4. Some Example Functions --
5.4.1. Guess the Number --
5.4.2. Function with Arguments --
5.5. Classes and Methods --
5.5.1. S3 Class and Method Example --
5.5.2. S3 Methods for Existing Classes --
6.1. Discrete Probability Distributions --
6.2. Binomial Distribution --
6.2.1. Poisson Distribution --
6.2.2. Some Other Discrete Distributions --
6.3. Continuous Probability Distributions --
6.3.1. Normal Distribution --
6.3.2. t Distribution --
6.3.3. t distribution --
6.3.4. Chi-Square Distribution --
References --
7.1. Working with One-Way Tables --
7.2. Working with Two-Way Tables --
8.1. Central Tendency --
8.1.1. Mean --
8.1.2. Median --
8.1.3. Mode --
8.2. Variability --
8.2.1. Range --
8.2.2. Variance and Standard Deviation --
8.3. Boxplots and Stem-and-Leaf Displays --
8.4. Using the fBasics Package for Summary Statistics --
References --
9.1. Creating Effective Graphics --
9.2. Graphing Nominal and Ordinal Data --
9.3. Graphing Scale Data --
9.3.1. Boxplots Revisited --
9.3.2. Histograms and Dotplots --
9.3.3. Frequency Polygons and Smoothed Density Plots --
9.3.4. Graphing Bivariate Data --
References --
10.1. Estimation and Confidence Intervals --
10.1.1. Confidence Intervals for Means --
10.1.2. Confidence Intervals for Proportions --
10.1.3. Confidence Intervals for the Variance --
10.2. Hypothesis Tests with One Sample --
10.3. Hypothesis Tests with Two Samples --
References --
11.1. Need for Modern Statistical Methods --
11.2. Modern Alternative to the Traditional tTest --
11.3. Bootstrapping --
11.4. Permutation Tests --
References --
12.1. Some Brief Background --
12.2. One-Way ANOVA --
12.3. Two-Way ANOVA --
12.3.1. Repeated-Measures ANOVA --
> results <- aov (fitness --
time + Error (id/time), data = repeated) --
12.3.2. Mixed-Model ANOVA --
References --
13.1. Covariance and Correlation --
13.2. Linear Regression: Bivariate Case --
13.3. Extended Regression Example: Stock Screener --
13.3.1. Quadratic Model: Stock Screener --
13.3.2. Note on Time Series --
13.4. Confidence and Prediction Intervals --
References --
14.1. Conceptual Statistics of Multiple Regression --
14.2. GSS Multiple Regression Example --
14.2.1. Exploratory Data Analysis --
14.2.2. Linear Model (the First) --
14.2.3. Adding the Next Predictor --
14.2.4. Adding More Predictors --
14.2.5. Presenting Results --
14.3. Final Thoughts --
References --
15.1. Mathematics of Logistic Regression --
15.2. Generalized Linear Models --
15.3. Example of Logistic Regression --
15.3.1. What If We Tried a Linear Model on Age? --
15.3.2. Seeing If Age Might Be Relevant with Chi Square --
15.3.3. Fitting a Logistic Regression Model --
15.3.4. Mathematics of Linear Scaling of Data --
15.3.5. Logit Model with Rescaled Predictor --
15.3.6. Multivariate Logistic Regression --
15.4. Ordered Logistic Regression --
15.4.1. Parallel Ordered Logistic Regression --
15.4.2. Non-Parallel Ordered Logistic Regression --
15.5. Multinomial Regression --
References --
16.1. Philosophy of Parameters --
16.2. Nonparametric Tests --
16.2.1. Wilcoxon-Signed-Rank Test --
16.2.2. Spearman's Rho --
16.2.3. Kruskal-Wallis Test --
16.2.4. One-Way Test --
16.3. Bootstrapping --
16.3.1. Examples from mtcars --
16.3.2. Bootstrapping Confidence Intervals --
16.3.3. Examples from GSS --
16.4. Final Thought --
References --
17.1. Required Packages --
17.2. Univariate Plots --
17.3. Customizing and Polishing Plots --
17.4. Multivariate Plots --
17.5. Multiple Plots --
17.6. Three-Dimensional Graphs --
References --
18.1. Data --
18.2. Parallel Processing --
18.2.1. Other Parallel Processing Approaches --
References --
19.1. Installing Needed Packages and Software --
19.1.1. Java --
19.1.2. PDF Software --
19.1.3. R Packages --
19.1.4. Some Needed Files --
19.2. Text Mining --
19.2.1. Word Clouds and Transformations --
19.2.2. PDF Text Input --
19.2.3. Google News Input --
19.2.4. Topic Models --
19.3. Final Thoughts --
References --
Epigraphy in Islamic tradition --
Use of inscriptions in Islamic architecture --
Emergence of Islamic epigraphy --
Importance of Islamic epigraphy --
Thematic variety of Islamic inscriptions --
Use of inscriptions as legal deeds --
Globalization and cultural continuity of the Islamic world: comparison of some inscriptions of Bengal with those of Andalusia --
Diversity of materials and features in Bengal inscriptions --
Comparison of Islamic inscriptions with Sanskrit inscriptions in Bengal --
Some conclusive remarks --
land --
advent of Islam and the Bengal hinterland --
Merchants and the faith: early Islamic contacts with Bengal --
Muslim conquest of Bengal and the beginning of Islamic consolidation --
emergence of the independent Sultanate and the spread of Islamic culture --
From syncretistic tradition to Islamic reassertion: the mighty Mughals and the British Raj --
Royalty and ruling establishment --
Commerce and maritime activities --
Mosques: the nucleus of Islamic society --
role of 'ulama' and madrasas in the transmission of knowledge --
Titles in Islamic culture and their historical importance --
Inscriptions of the Khalji chiefs --
Inscriptions of the early rulers appointed by the Delhi Sultans --
Inscriptions of the Balbani rulers --
Inscriptions of the early Ilyas Shahi rulers --
Inscriptions of the indigenous Bengali sultans (Sultan Jalal al-Din Muhammad Shah and his son) --
Inscriptions of the later Ilyas Shahi rulers (the restored dynasty) --
Inscriptions of the so-called Habashi rulers of Abyssinian origin.
Series Title: Expert's voice in programming.
Responsibility: Joshua F. Wiley, Larry A. Pace.

Abstract:

Beginning R, Second Edition is a hands-on book showing howto use the R language, write and save R scripts, read in data files, and writecustom statistical functions as well as use built in functions.  Read more...

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