國立高雄大學圖資館 |

登入

回首頁 到查詢結果 [ subject:"Statistical Software." ]

Introduction to statistics and data analysiswith exercises, solutions and applications in R /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to statistics and data analysisby Christian Heumann, Michael Schomaker, Shalabh.
其他題名:	with exercises, solutions and applications in R /
作者:	Heumann, Christian.
其他作者:	Schomaker, Michael.
出版者:	Cham :Springer International Publishing :2022.
面頁冊數:	xvii, 584 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	Statistics.
電子資源:	https://doi.org/10.1007/978-3-031-11833-3
ISBN:	9783031118333$q(electronic bk.)

Introduction to statistics and data analysiswith exercises, solutions and applications in R /
Heumann, Christian.

Introduction to statistics and data analysiswith exercises, solutions and applications in R /[electronic resource] :by Christian Heumann, Michael Schomaker, Shalabh. - Second edition. - Cham :Springer International Publishing :2022. - xvii, 584 p. :ill. (some col.), digital ;24 cm.

Part I Descriptive Statistics: Introduction and Framework -- Frequency Measures and Graphical Representation of Data -- Measures of Central Tendency and Dispersion -- Association of Two Variables -- Part I Probability Calculus: Combinatorics -- Elements of Probability Theory -- Random Variables -- Probability Distributions -- Part III Inductive Statistics: Inference -- Hypothesis Testing -- Linear Regression -- Logistic Regression -- Part IV Additional Topics Simple Random Sampling and Bootstrapping -- Causality -- Part V Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries.

Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.

ISBN: 9783031118333$q(electronic bk.)

Standard No.: 10.1007/978-3-031-11833-3doiSubjects--Topical Terms:

182057
Statistics.

LC Class. No.: QA276

Dewey Class. No.: 519.5

Introduction to statistics and data analysiswith exercises, solutions and applications in R /
LDR:02567nmm a2200337 a 4500 001 634554
003 DE-He213
005 20230130103436.0
006 m d
007 cr nn 008maaau
008 230529s2022 sz s 0 eng d
020 $a 9783031118333$q(electronic bk.)
020 $a 9783031118326$q(paper)
024 7 $a 10.1007/978-3-031-11833-3 $2 doi
035 $a 978-3-031-11833-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA276
072 7 $a PBT $2 bicssc
072 7 $a MAT029000 $2 bisacsh
072 7 $a PBT $2 thema
082 0 4 $a 519.5 $2 23
090 $a QA276 $b .H593 2022
100 1 $a Heumann, Christian. $3 285990
245 1 0 $a Introduction to statistics and data analysis $h [electronic resource] : $b with exercises, solutions and applications in R / $c by Christian Heumann, Michael Schomaker, Shalabh.
250 $a Second edition.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xvii, 584 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Part I Descriptive Statistics: Introduction and Framework -- Frequency Measures and Graphical Representation of Data -- Measures of Central Tendency and Dispersion -- Association of Two Variables -- Part I Probability Calculus: Combinatorics -- Elements of Probability Theory -- Random Variables -- Probability Distributions -- Part III Inductive Statistics: Inference -- Hypothesis Testing -- Linear Regression -- Logistic Regression -- Part IV Additional Topics Simple Random Sampling and Bootstrapping -- Causality -- Part V Appendices: Introduction to R -- Solutions to Exercises -- Technical Appendix -- Visual Summaries.
520 $a Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
650 0 $a Statistics. $3 182057
650 0 $a R (Computer program language) $x Statistical methods. $3 544756
650 0 $a Econometrics. $3 182271
650 0 $a Macroeconomics. $3 183168
650 1 4 $a Statistical Theory and Methods. $3 274054
650 2 4 $a Data Analysis and Big Data. $3 913147
650 2 4 $a Applied Statistics. $3 805583
650 2 4 $a Statistical Software. $3 925687
700 1 $a Schomaker, Michael. $3 766723
700 0 $a Shalabh. $3 285991
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-031-11833-3
950 $a Mathematics and Statistics (SpringerNature-11649)