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Introduction to statistics using R /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Introduction to statistics using R // Mustapha Akinkunmi.
Author:	Akinkunmi, Mustapha,
Description:	1 PDF (xix, 215 pages) :illustrations (some color). :
Notes:	Part of: Synthesis digital library of engineering and computer science
Subject:	Mathematical statistics - Data processing. -
Online resource:	https://ieeexplore.ieee.org/servlet/opac?bknumber=8782980
Online resource:	https://doi.org/10.2200/S00899ED1V01Y201902MAS024
ISBN:	9781681735108

Introduction to statistics using R /
Akinkunmi, Mustapha,

Introduction to statistics using R /Mustapha Akinkunmi. - 1 PDF (xix, 215 pages) :illustrations (some color). - Synthesis lectures on mathematics and statistics,#241938-1751 ;. - Synthesis digital library of engineering and computer science..

Part of: Synthesis digital library of engineering and computer science

Includes bibliographical references (page 213).

1. Introduction to statistical analysis -- 1.1. Scales of measurements -- 1.2. Data, data collection, and data presentation -- 1.3. Data groupings -- 1.4. Methods of visualizing data -- 1.5. Exploring data analysis (EDA) -- 1.6. Exercises

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

Compendex

Introduction to Statistics Using R is organized into 13 major chapters. Each chapter is broken down into many digestible subsections in order to explore the objectives of the book. There are many real-life practical examples in this book and each of the examples is written in R codes to acquaint the readers with some statistical methods while simultaneously learning R scripts.

Mode of access: World Wide Web.

ISBN: 9781681735108

Standard No.: 10.2200/S00899ED1V01Y201902MAS024doiSubjects--Uniform Titles:

R (Computer program language)
Subjects--Topical Terms:

558446
Mathematical statistics
--Data processing.Subjects--Index Terms:

descriptive statisticsIndex Terms--Genre/Form:

554714
Electronic books.

LC Class. No.: QA276.45.R3 / A555 2019eb

Dewey Class. No.: 519.50285/5133

Introduction to statistics using R /
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020 $z 9781681735115 $q hardcover
020 $z 9781681735092 $q paperback
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100 1 $a Akinkunmi, Mustapha, $e author. $3 1253121
245 1 0 $a Introduction to statistics using R / $c Mustapha Akinkunmi.
264 1 $a [San Rafael, California] : $b Morgan & Claypool, $c [2019]
300 $a 1 PDF (xix, 215 pages) : $b illustrations (some color).
336 $a text $2 rdacontent
337 $a electronic $2 isbdmedia
338 $a online resource $2 rdacarrier
490 1 $a Synthesis lectures on mathematics and statistics, $x 1938-1751 ; $v #24
500 $a Part of: Synthesis digital library of engineering and computer science
504 $a Includes bibliographical references (page 213).
505 0 $a 1. Introduction to statistical analysis -- 1.1. Scales of measurements -- 1.2. Data, data collection, and data presentation -- 1.3. Data groupings -- 1.4. Methods of visualizing data -- 1.5. Exploring data analysis (EDA) -- 1.6. Exercises
505 2 $a 2. Introduction to R software -- 2.1. How to download and install R -- 2.2. Using R for descriptive statistical and plots -- 2.3. Basics of R -- 2.4. Basic operations in R -- 2.5. Data exploration -- 2.6. Exercises
505 2 $a 3. Descriptive data -- 3.1. Central tendency -- 3.2. Measure of dispersion -- 3.3. Shapes of the distribution--symmetric and asymmetric -- 3.4. Exercises
505 2 $a 4. Basic probability concepts -- 4.1. Experiment, outcome, and sample space -- 4.2. Elementary events -- 4.3. Complementary events -- 4.4. Mutually exclusive events -- 4.5. Mutually inclusive events -- 4.6. Venn diagram -- 4.7. Probability -- 4.8. Axioms of probability -- 4.9. Basic properties of probability -- 4.10. Independent events and dependent events -- 4.11. Multiplication rule of probability -- 4.12. Conditional probabilities -- 4.13. Computation of probability in R -- 4.14. Exercises
505 2 $a 5. Discrete probability distributions -- 5.1. Probability mass distribution -- 5.2. Expected value and variance of a discrete random variable -- 5.3. Binomial probability distribution -- 5.4. Expected value and variance of a binomial distribution -- 5.5. Solve problems involving binomial distribution using R -- 5.6. Exercises
505 2 $a 6. Continuous probability distributions -- 6.1. Normal distribution and standardized normal distribution -- 6.2. Standard normal score (z-score) -- 6.3. Approximate normal distribution to the binomial distribution -- 6.4. Use of the normal distribution in business problem solving using R -- 6.5. Exercises
505 2 $a 7. Other continuous probability distributions -- 7.1. Student-t distribution -- 7.2. Chi-square distribution -- 7.3. F-Distribution -- 7.4. Exercises
505 2 $a 8. Sampling and sampling distribution -- 8.1. Probability and non-probability sampling -- 8.2. Probability sampling techniques--simple random, systematic, stratified, and cluster samples -- 8.3. Non-probability sampling techniques -- 8.4. Sampling distribution of the mean -- 8.5. Central limit theorem and its significance -- 8.6. Exercises
505 2 $a 9. Confidence intervals for single population mean and proportion -- 9.1. Point estimates and interval estimates -- 9.2. Confidence intervals for mean -- 9.3. Confidence intervals for proportion -- 9.4. Calculating the sample size -- 9.5. Factors that determine margin of error -- 9.6. Exercises
505 2 $a 10. Hypothesis testing for single population mean and proportion -- 10.1. Null and alternative hypotheses -- 10.2. Type I and type II errors -- 10.3. Acceptance and rejection regions -- 10.4. Hypothesis testing procedures -- 10.5. Exercises
505 2 $a 11. Regression analysis and correlation -- 11.1. Construction of line fit plots -- 11.2. Types of regression analysis -- 11.3. Multiple linear regression -- 11.4. Pearson correlation coefficient -- 11.5. Exercises
505 2 $a 12. Poisson distribution -- 12.1. Poisson distribution and its properties -- 12.2. Mean and variance of a Poisson distribution -- 12.3. Application of Poisson distribution -- 12.4. Poisson to approximate the binomial -- 12.5. Exercises
505 2 $a 13. Uniform distributions -- 13.1. Uniform distribution and its properties -- 13.2. Mean and variance of a uniform distribution -- 13.3. Exercises.
506 $a Abstract freely available; full-text restricted to subscribers or individual document purchasers.
510 0 $a Compendex
510 0 $a INSPEC
510 0 $a Google scholar
510 0 $a Google book search
520 $a Introduction to Statistics Using R is organized into 13 major chapters. Each chapter is broken down into many digestible subsections in order to explore the objectives of the book. There are many real-life practical examples in this book and each of the examples is written in R codes to acquaint the readers with some statistical methods while simultaneously learning R scripts.
530 $a Also available in print.
538 $a Mode of access: World Wide Web.
538 $a System requirements: Adobe Acrobat Reader.
588 $a Title from PDF title page (viewed on July 31, 2019).
630 0 0 $a R (Computer program language) $3 1253122
650 0 $a Mathematical statistics $x Data processing. $3 558446
650 0 $a Statistics $x Data processing. $3 672142
653 $a descriptive statistics
653 $a probability distributions
653 $a sampling distribution
653 $a hypothesis testing
653 $a regression analysis
653 $a correlation analysis
653 $a confidence interval
655 0 $a Electronic books. $2 local $3 554714
776 0 8 $i Print version: $z 9781681735115 $z 9781681735092
830 0 $a Synthesis digital library of engineering and computer science. $3 598254
830 0 $a Synthesis lectures on mathematics and statistics ; $v #26. $3 1253098
856 4 2 $3 Abstract with links to resource $u https://ieeexplore.ieee.org/servlet/opac?bknumber=8782980
856 4 0 $3 Abstract with links to full text $u https://doi.org/10.2200/S00899ED1V01Y201902MAS024