Muutke küpsiste eelistusi

E-raamat: R Companion for the Third Edition of The Fundamentals of Political Science Research

(Texas A & M University), (Texas A & M University)
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 10-Jun-2021
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781108653268
Teised raamatud teemal:
  • Formaat - EPUB+DRM
  • Hind: 25,92 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
R Companion for the Third Edition of The Fundamentals of Political Science ResearchSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 10-Jun-2021
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781108653268
Teised raamatud teemal:

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

This workbook teaches students how to use the popular R statistical software program to assess causal relationships using real political science data. It parallels the main Kellstedt and Whitten text, which allows students to apply the lessons and techniques they learn in each chapter in a statistical software setting.

An R Companion for the Third Edition of The Fundamentals of Political Science Research offers students a chance to delve into the world of R using real political data sets and statistical analysis techniques directly from Paul M. Kellstedt and Guy D. Whitten's best-selling textbook. Built in parallel with the main text, this workbook teaches students to apply the techniques they learn in each chapter by reproducing the analyses and results from each lesson using R. Students will also learn to create all of the tables and figures found in the textbook, leading to an even greater mastery of the core material. This accessible, informative, and engaging companion walks through the use of R step-by-step, using command lines and screenshots to demonstrate proper use of the software. With the help of these guides, students will become comfortable creating, editing, and using data sets in R to produce original statistical analyses for evaluating causal claims. End-of-chapter exercises encourage this innovation by asking students to formulate and evaluate their own hypotheses.

Muu info

Teaches students how to use R to conduct the statistical analyses most commonly used in political science.
Preface xi
List of Figures
xiii
1 The Scientific Study of Politics
1(8)
1.1 Overview
1(1)
1.2 "A Workbook? Why Is There a Workbook?"
1(1)
1.2.1 Reading Commands in This Workbook
2(1)
1.3 Getting Started with R and RStudio
2(6)
1.3.1 Launching RStudio
3(1)
1.3.2 Getting R to Do Things
3(3)
1.3.3 Initially Examining Data in R
6(1)
1.3.4 Adding Notes to Script Files and Saving Them
7(1)
1.4 Exercises
8(1)
2 The Art of Theory Building
9(10)
2.1 Overview
9(1)
2.2 R Packages
9(1)
2.3 Examining Variation across Time and across Space
10(4)
2.3.1 Producing a Bar Graph for Examining Cross-Section Variation
11(2)
2.3.2 Producing a Connected Plot for Examining Time-Series Variation
13(1)
2.4 Using Google Scholar to Search the Literature Effectively
14(4)
2.5 Wrapping Up
18(1)
2.6 Exercises
18(1)
3 Evaluating Causal Relationships
19(3)
3.1 Overview
19(1)
3.2 Exercises
19(3)
4 Research Design
22(2)
4.1 Overview
22(1)
4.2 Exercises
22(2)
5 Measuring Concepts of Interest
24(3)
5.1 Overview
24(1)
5.2 Exercises
24(3)
6 Getting to Know Your Data
27(8)
6.1 Overview
27(1)
6.2 Describing Categorical and Ordinal Variables
27(3)
6.3 Describing Continuous Variables
30(2)
6.4 Putting Statistical Output into Tables, Documents, and Presentations
32(1)
6.5 Exercises
33(2)
7 Probability and Statistical Inference
35(7)
7.1 Overview
35(1)
7.2 Dice Rolling in R
35(5)
7.3 Exercises
40(2)
8 Bivariate Hypothesis Testing
42(8)
8.1 Overview
42(1)
8.2 Tabular Analysis
42(3)
8.2.1 Generating Test Statistics
43(1)
8.2.2 Putting Tabular Results into Papers
44(1)
8.3 Difference of Means
45(1)
8.3.1 Examining Differences Graphically
45(1)
8.3.2 Generating Test Statistics
45(1)
8.4 Correlation Coefficients
46(2)
8.4.1 Producing Scatter Plots
46(1)
8.4.2 Generating Covariance Tables and Test Statistics
47(1)
8.5 Exercises
48(2)
9 Two-Variable Regression Models
50(3)
9.1 Overview
50(1)
9.2 Estimating a Two-Variable Regression
50(1)
9.3 Graphing a Two-Variable Regression
51(1)
9.4 Exercises
52(1)
10 Multiple Regression: The Basics
53(5)
10.1 Overview
53(1)
10.2 Estimating a Multiple Regression
53(1)
10.3 From Regression Output to Table- Making Only One Type of Comparison
54(2)
10.3.1 Comparing Models with the Same Sample of Data, but Different Specifications
54(1)
10.3.2 Comparing Models with the Same Specification, but Different Samples of Data
55(1)
10.4 Standardized Coefficients
56(1)
10.5 Exercises
56(2)
11 Multiple Regression Model Specification
58(8)
11.1 Overview
58(1)
11.2 Dummy Variables
58(3)
11.2.1 Creating New Variables
58(2)
11.2.2 Estimating a Multiple Regression Model with a Single Dummy Independent Variable
60(1)
11.2.3 Estimating a Multiple Regression Model with Multiple Dummy Independent Variables
60(1)
11.3 Dummy Variables in Interactions
61(1)
11.4 Post-estimation Diagnostics in R for OLS
61(3)
11.4.1 Identifying Outliers and Influential Cases in OLS
61(3)
11.5 Exercises
64(2)
12 Limited Dependent Variables and Time-Series Data
66(5)
12.1 Overview
66(1)
12.2 Models with Dummy Dependent Variables
66(4)
12.3 Exercises
70(1)
Bibliography 71(2)
Index 73
Paul M. Kellstedt is Professor of Political Science at Texas A&M University. He is the author of The Mass Media and the Dynamics of American Racial Attitudes (Cambridge, 2003), winner of Harvard University's John F. Kennedy School of Government's 2004 Goldsmith Book Prize. In addition, he has published numerous articles in a variety of leading journals. He is the Editor-in-chief of Political Science Research and Methods, the flagship journal of the European Political Science Association. Guy D. Whitten is Cullen-McFadden Professor of Political Science, as well as Director of the European Union Center, at Texas A&M University. He has published a variety of articles in leading peer-reviewed journals. He is on the editorial boards of Political Analysis and Political Science Research and Methods.
Lisainfo e-raamatute kohta Lisainfo e-raamatute kohta
Püsilink: https://www.kriso.ee/db/97811086532686e.html
Märksõnad: