東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Modern survey analysis = using Pytho...

Paczkowski, Walter R.

FindBook

Google Book

Amazon

博客來

Modern survey analysis = using Python for deeper insights /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Modern survey analysis/ by Walter R. Paczkowski.
其他題名:	using Python for deeper insights /
作者:	Paczkowski, Walter R.
出版者:	Cham :Springer International Publishing : : 2022.,
面頁冊數:	xxvi, 347 p. :ill. (some col.), digital ;24 cm.
內容註:	1. Introduction -- 2. Understanding the structure of survey data -- 3. Shallow analyses of survey data -- 4. Deep analyses of survey data -- 5. Conclusion and wrap-up.
Contained By:	Springer Nature eBook
標題:	Market surveys - Data processing. -
電子資源:	https://doi.org/10.1007/978-3-030-76267-4
ISBN:	9783030762674

Modern survey analysis = using Python for deeper insights /
Paczkowski, Walter R.

Modern survey analysisusing Python for deeper insights /[electronic resource] :by Walter R. Paczkowski. - Cham :Springer International Publishing :2022. - xxvi, 347 p. :ill. (some col.), digital ;24 cm.

1. Introduction -- 2. Understanding the structure of survey data -- 3. Shallow analyses of survey data -- 4. Deep analyses of survey data -- 5. Conclusion and wrap-up.

This book develops survey data analysis tools in Python, to create and analyze cross-tab tables and data visuals, weight data, perform hypothesis tests, and handle special survey questions such as Check-all-that-Apply. In addition, the basics of Bayesian data analysis and its Python implementation are presented. Since surveys are widely used as the primary method to collect data, and ultimately information, on attitudes, interests, and opinions of customers and constituents, these tools are vital for private or public sector policy decisions. As a compact volume, this book uses case studies to illustrate methods of analysis essential for those who work with survey data in either sector. It focuses on two overarching objectives: Demonstrate how to extract actionable, insightful, and useful information from survey data; and Introduce Python and Pandas for analyzing survey data.

ISBN: 9783030762674

Standard No.: 10.1007/978-3-030-76267-4doiSubjects--Topical Terms:

3606340
Market surveys
--Data processing.

LC Class. No.: HF5415 / .P33 2022

Dewey Class. No.: 658.83

Modern survey analysis = using Python for deeper insights /
LDR:02110nmm a2200349 a 4500 001 2304256
003 DE-He213
005 20220911170555.0
006 m d
007 cr nn 008maaau
008 230409s2022 sz s 0 eng d
020 $a 9783030762674 $q (electronic bk.)
020 $a 9783030762667 $q (paper)
024 7 $a 10.1007/978-3-030-76267-4 $2 doi
035 $a 978-3-030-76267-4
040 $a GP $c GP
041 0 $a eng
050 4 $a HF5415 $b .P33 2022
072 7 $a PBT $2 bicssc
072 7 $a K $2 bicssc
072 7 $a BUS061000 $2 bisacsh
072 7 $a PBT $2 thema
072 7 $a K $2 thema
082 0 4 $a 658.83 $2 23
090 $a HF5415 $b .P122 2022
100 1 $a Paczkowski, Walter R. $3 3511009
245 1 0 $a Modern survey analysis $h [electronic resource] : $b using Python for deeper insights / $c by Walter R. Paczkowski.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xxvi, 347 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a 1. Introduction -- 2. Understanding the structure of survey data -- 3. Shallow analyses of survey data -- 4. Deep analyses of survey data -- 5. Conclusion and wrap-up.
520 $a This book develops survey data analysis tools in Python, to create and analyze cross-tab tables and data visuals, weight data, perform hypothesis tests, and handle special survey questions such as Check-all-that-Apply. In addition, the basics of Bayesian data analysis and its Python implementation are presented. Since surveys are widely used as the primary method to collect data, and ultimately information, on attitudes, interests, and opinions of customers and constituents, these tools are vital for private or public sector policy decisions. As a compact volume, this book uses case studies to illustrate methods of analysis essential for those who work with survey data in either sector. It focuses on two overarching objectives: Demonstrate how to extract actionable, insightful, and useful information from survey data; and Introduce Python and Pandas for analyzing survey data.
650 0 $a Market surveys $x Data processing. $3 3606340
650 0 $a Python (Computer program language) $3 729789
650 1 4 $a Statistics in Business, Management, Economics, Finance, Insurance. $3 3538572
650 2 4 $a Data and Information Visualization. $3 3538847
650 2 4 $a Marketing. $3 536353
650 2 4 $a Statistics and Computing. $3 3594429
650 2 4 $a Data Science. $3 3538937
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-030-76267-4
950 $a Mathematics and Statistics (SpringerNature-11649)