The document discusses a conference on business analytics and data science in Thailand that included several presentations and topics:
1) Using data science to predict the results of Thailand's upcoming election and factors like social, economic, geographic, and demographic variables that could influence election outcomes.
2) Building spatial regression models to predict election results based on past voting data and other metrics.
3) One presentation discussed building a spatial negative binomial regression model to predict Thailand's 2011 election results based on 2005 and 2007 election data as well as socioeconomic and demographic variables.
Bsc vietnam outlook 2020 2021 (english) colour of the year (final sars-Cov2 r...Long Tran
a quick overview of Vietnam Stock market and economy in 2020 2021 from BIDV securities Company (BSC).
Top 3 Research house in Vietnam (AsiaMoney Broker Poll 2019)
Bsc vietnam outlook 2020 2021 (english) colour of the year (final sars-Cov2 r...Long Tran
a quick overview of Vietnam Stock market and economy in 2020 2021 from BIDV securities Company (BSC).
Top 3 Research house in Vietnam (AsiaMoney Broker Poll 2019)
Thailand household's disparity of socioeconomic statust: A cluster analysis โ...BAINIDA
Thailand household's disparity of socioeconomic statust: A cluster analysis โดย ประภาศรี เลิศเลอเกียรติ อาจารย์ ดร. อานนท์ ศักดิ์วรวิชญ์
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
การเกื้อหนุนบิดามารดาสูงอายุวัยปลายจากบุตรวัยผู้ใหญ่ โดย ร.ท.กนกกร ศักดิ์แหลมเงิน รศ.ดร.เดือนเพ็ญ ธีรวรรณวิวัฒน์
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Current trends in information security โดย ผศ.ดร.ปราโมทย์ กั่วเจริญBAINIDA
Current trends in information security โดย ผศ.ดร.ปราโมทย์ กั่วเจริญ
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Text Mining in Business Intelligence โดย รศ.ดร.โอม ศรนิลBAINIDA
Text Mining in Business Intelligence โดย รศ.ดร.โอม ศรนิล
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Agile Development for Startup โดย ผศ.ดร.รัฐกร พูลทรัพย์BAINIDA
Agile Development for Startup โดย ผศ.ดร.รัฐกร พูลทรัพย์
คณะสถิติประยุกต์ สถาบันบัณฑิตพัฒนบริหารศาสตร์ ร่วมกับ Data Science Thailand ร่วมกันจัดงาน The First NIDA Business Analytics and Data Sciences Contest/Conference
DevOps : Integrate, Deliver and Deploy continuously with Visual Studio Team S...BAINIDA
DevOps : Integrate, Deliver and Deploy continuously with Visual Studio Team Services โดย เฉลิมวงศ์ วิจิตรปิยะกุล MVP, Microsoft Thailand
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Proportional Hazard Model for Predicting Stroke Mortality โดย พิมพ์ชนก พุฒขาว...BAINIDA
Proportional Hazard Model for Predicting Stroke Mortality โดย พิมพ์ชนก พุฒขาว รศ.ดร.เดือนเพ็ญ ธีรวรรณวิวัฒน์
ใน Demographic and Actuarial Analytics .ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Data Analytics in your IoT SolutionFukiat Julnual, Technical Evangelist, Mic...BAINIDA
Data Analytics in your IoT SolutionFukiat Julnual, Technical Evangelist, Microsoft (Thailand) Limited ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
สถิติทางการกับการพัฒนาประเทศ บทบาทของสำนักงานสถิติแห่งชาติ โดย นางหทัยชนก พรรคเจริญ ดร. บงกช วิบูลย์ธนานันต์
ในงาน The First Business Analytics and Data Sciences Conference
Face recognition and modeling โดย ผศ.ดร.ธนาสัย สุคนธ์พันธุ์BAINIDA
Face recognition and modeling โดย ผศ.ดร.ธนาสัย สุคนธ์พันธุ์
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
From fraudulence to adversarial learning จรัล งามวิโรจน์เจริญ chief data sci...BAINIDA
From fraudulence to adversarial learning จรัล งามวิโรจน์เจริญ chief data scientist and VP of Data Innovation Lab at Sertis, former lead data scientist of Booz Allen Hamilton
Internet of Things and Complex event processing (CEP)/Data fusionBAINIDA
Internet of Things and Complex event processing (CEP)/Data fusion
ปริญญา หิรัญปัณฑาพร
Data Analytics/Advanced Analytics ที่ Allianz Ayudhya
วทม (NIDA)
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Face recognition and deep learning โดย ดร. สรรพฤทธิ์ มฤคทัต NECTECBAINIDA
Face recognition and deep learning โดย ดร. สรรพฤทธิ์ มฤคทัต NECTEC
คณะสถิติประยุกต์ สถาบันบัณฑิตพัฒนบริหารศาสตร์ ร่วมกับ Data Science Thailand ร่วมกันจัดงาน The First NIDA Business Analytics and Data Sciences Contest/Conference
Big data technology by Data Sciences Thailand ในงาน THE FIRST NIDA BUSINESS A...BAINIDA
Big data technology by Data Sciences Thailand ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Big Data Analytics to Enhance Security คุณอนพัทย์ พิพัฒน์กิติบดี Technical Ma...BAINIDA
Big Data Analytics to Enhance Security คุณอนพัทย์ พิพัฒน์กิติบดี Technical Manager, Stelligence ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Survey of Myanmar Public Opinion March 9 –April 1- 2017-IRI Releases Survey o...MYO AUNG Myanmar
Survey of Burma/Myanmar Public Opinion-March 9 – April 1, 2017-IRI Releases Survey of Burmese Public Opinion
AUGUST 22, 2017
Yangon, Myanmar—The International Republican Institute’s (IRI) Center for Insights in Survey Research today released a new poll surveying Burmese public opinion.
The survey sample size consisted of 3,000 citizens of Burma, with a margin of error of plus or minus 1.8 percent. IRI has worked in Burma since 2012, and provided assistance to Burmese civil society organizations for more than 25 years. IRI’s program is dedicated to strengthening Burma’s representative institutions and civil society organizations through public opinion polling, workshops and consultations that allow policymakers to more effectively address citizens’ concerns.
http://www.iri.org/resource/iri-releases-survey-burmese-public-opinion
https://burmese.voanews.com/a/myanmar-survey-results/3997693.html
Mixed results for Aung San Suu Kyi’s government in first major survey
http://www.iri.org/sites/default/files/flip_docs/2014%20April%203%20Survey%20of%20Burma%20Public%20Opinion,%20December%2024,%202013-February%201,%202014.pdf
Survey of Burma Public Opinion-December 24, 2013 - February 1, 2014
Introduction
As the Jubilee administration nears the half-way mark in its term, Ipsos’ most recent survey included questions on a number of issues that are continuing to occupy public, and government, attention. In this Media Release, we cover the following in the Education sector: (1) The laptop project, (2) School-ranking, (3) Teachers’ Pay Demands.
Thailand household's disparity of socioeconomic statust: A cluster analysis โ...BAINIDA
Thailand household's disparity of socioeconomic statust: A cluster analysis โดย ประภาศรี เลิศเลอเกียรติ อาจารย์ ดร. อานนท์ ศักดิ์วรวิชญ์
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
การเกื้อหนุนบิดามารดาสูงอายุวัยปลายจากบุตรวัยผู้ใหญ่ โดย ร.ท.กนกกร ศักดิ์แหลมเงิน รศ.ดร.เดือนเพ็ญ ธีรวรรณวิวัฒน์
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Current trends in information security โดย ผศ.ดร.ปราโมทย์ กั่วเจริญBAINIDA
Current trends in information security โดย ผศ.ดร.ปราโมทย์ กั่วเจริญ
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Text Mining in Business Intelligence โดย รศ.ดร.โอม ศรนิลBAINIDA
Text Mining in Business Intelligence โดย รศ.ดร.โอม ศรนิล
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Agile Development for Startup โดย ผศ.ดร.รัฐกร พูลทรัพย์BAINIDA
Agile Development for Startup โดย ผศ.ดร.รัฐกร พูลทรัพย์
คณะสถิติประยุกต์ สถาบันบัณฑิตพัฒนบริหารศาสตร์ ร่วมกับ Data Science Thailand ร่วมกันจัดงาน The First NIDA Business Analytics and Data Sciences Contest/Conference
DevOps : Integrate, Deliver and Deploy continuously with Visual Studio Team S...BAINIDA
DevOps : Integrate, Deliver and Deploy continuously with Visual Studio Team Services โดย เฉลิมวงศ์ วิจิตรปิยะกุล MVP, Microsoft Thailand
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Proportional Hazard Model for Predicting Stroke Mortality โดย พิมพ์ชนก พุฒขาว...BAINIDA
Proportional Hazard Model for Predicting Stroke Mortality โดย พิมพ์ชนก พุฒขาว รศ.ดร.เดือนเพ็ญ ธีรวรรณวิวัฒน์
ใน Demographic and Actuarial Analytics .ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Data Analytics in your IoT SolutionFukiat Julnual, Technical Evangelist, Mic...BAINIDA
Data Analytics in your IoT SolutionFukiat Julnual, Technical Evangelist, Microsoft (Thailand) Limited ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
สถิติทางการกับการพัฒนาประเทศ บทบาทของสำนักงานสถิติแห่งชาติ โดย นางหทัยชนก พรรคเจริญ ดร. บงกช วิบูลย์ธนานันต์
ในงาน The First Business Analytics and Data Sciences Conference
Face recognition and modeling โดย ผศ.ดร.ธนาสัย สุคนธ์พันธุ์BAINIDA
Face recognition and modeling โดย ผศ.ดร.ธนาสัย สุคนธ์พันธุ์
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
From fraudulence to adversarial learning จรัล งามวิโรจน์เจริญ chief data sci...BAINIDA
From fraudulence to adversarial learning จรัล งามวิโรจน์เจริญ chief data scientist and VP of Data Innovation Lab at Sertis, former lead data scientist of Booz Allen Hamilton
Internet of Things and Complex event processing (CEP)/Data fusionBAINIDA
Internet of Things and Complex event processing (CEP)/Data fusion
ปริญญา หิรัญปัณฑาพร
Data Analytics/Advanced Analytics ที่ Allianz Ayudhya
วทม (NIDA)
ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Face recognition and deep learning โดย ดร. สรรพฤทธิ์ มฤคทัต NECTECBAINIDA
Face recognition and deep learning โดย ดร. สรรพฤทธิ์ มฤคทัต NECTEC
คณะสถิติประยุกต์ สถาบันบัณฑิตพัฒนบริหารศาสตร์ ร่วมกับ Data Science Thailand ร่วมกันจัดงาน The First NIDA Business Analytics and Data Sciences Contest/Conference
Big data technology by Data Sciences Thailand ในงาน THE FIRST NIDA BUSINESS A...BAINIDA
Big data technology by Data Sciences Thailand ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Big Data Analytics to Enhance Security คุณอนพัทย์ พิพัฒน์กิติบดี Technical Ma...BAINIDA
Big Data Analytics to Enhance Security คุณอนพัทย์ พิพัฒน์กิติบดี Technical Manager, Stelligence ในงาน THE FIRST NIDA BUSINESS ANALYTICS AND DATA SCIENCES CONTEST/CONFERENCE จัดโดย คณะสถิติประยุกต์และ DATA SCIENCES THAILAND
Survey of Myanmar Public Opinion March 9 –April 1- 2017-IRI Releases Survey o...MYO AUNG Myanmar
Survey of Burma/Myanmar Public Opinion-March 9 – April 1, 2017-IRI Releases Survey of Burmese Public Opinion
AUGUST 22, 2017
Yangon, Myanmar—The International Republican Institute’s (IRI) Center for Insights in Survey Research today released a new poll surveying Burmese public opinion.
The survey sample size consisted of 3,000 citizens of Burma, with a margin of error of plus or minus 1.8 percent. IRI has worked in Burma since 2012, and provided assistance to Burmese civil society organizations for more than 25 years. IRI’s program is dedicated to strengthening Burma’s representative institutions and civil society organizations through public opinion polling, workshops and consultations that allow policymakers to more effectively address citizens’ concerns.
http://www.iri.org/resource/iri-releases-survey-burmese-public-opinion
https://burmese.voanews.com/a/myanmar-survey-results/3997693.html
Mixed results for Aung San Suu Kyi’s government in first major survey
http://www.iri.org/sites/default/files/flip_docs/2014%20April%203%20Survey%20of%20Burma%20Public%20Opinion,%20December%2024,%202013-February%201,%202014.pdf
Survey of Burma Public Opinion-December 24, 2013 - February 1, 2014
Introduction
As the Jubilee administration nears the half-way mark in its term, Ipsos’ most recent survey included questions on a number of issues that are continuing to occupy public, and government, attention. In this Media Release, we cover the following in the Education sector: (1) The laptop project, (2) School-ranking, (3) Teachers’ Pay Demands.
The nationwide TNS opinion poll was carried out between 15 and 20 January of 2013 by its local partner IPSC. The poll was commissioned by European Friends of Armenia (www.EuFoA.org) in order to contribute to a factual debate ahead of the elections. The sample size of the survey is 1,607.
The second nationwide TNS opinion poll was carried out between 31 January and 5 February 2013 by its local partner IPSC. The poll was commissioned by European Friends of Armenia (www.EuFoA.org) in order to contribute to a factual debate ahead of the elections. The sample size of the survey is 1,609.
The present paper makes an attempt to study the Financial Literacy lead to
Empowering the Socio-economic condition of Tribals through informationa
technology and its impact on the day to day life of the rural people. For this purpose
the questionnaire is developed and distributed . In our study we found that the
Information Technology ( IT) have made significant contribution in the life of the
tribal people in some areas and still long way to go . It changed the life style of the
people and a the rural people able to find new markets for their products .
A Product Management Case Study (Biswadeep Ghosh Hazra) - {IIM Calcutta}Biswadeep Ghosh Hazra
The Problem Statement was to create an app or any other tech-based solution which helps improve issues such as awareness and treatment related to depression and anxiety.
I created an application that had various sections- CBT, Meditation, Counselling and Mood Diary. The solution covered the following-
1. Use cases of the app
2. Target audience
3. App features
4. Mockups
5. Success Metrics
6. Prioritization
party list calculation visualization @ BADS@ Exploratory Data Analysis and Data Visualization @Graduate School of Applied Statistics, National Development of Administration, taught by Arnond Sakworawich, Ph.D.
วิทยาการข้อมูลสำหรับการแพทย์ บรรยายที่โรงพยาบาลชลบุรี วันที่ 21 มีนาคม 2561 เวลา 13.00-15.00 น
Data Science
Big Data
Data Science in Medicine & Health Care
Health and Bioinformatics
Data Science and Health Care Planning
Data Science and Health Care Prevention and Protection
Data Science and Medical Diagnosis
Data Science and Medical Care & Treatment
Data Engineering for Health Care
Financial time series analysis with R@the 3rd NIDA BADS conference by Asst. p...BAINIDA
Introduction to financial time series analysis, getting financial time series data through yahoo finance API with R, time series visualization, risk and return calculation for financial time series data, autoregressive integrated moving average models with R code and applications in financial time series.
Data science and big data for business and industrial applicationBAINIDA
Data science and big data for business and industrial application บรรยายที่วิทยาลัยเทคโนโลยีจิตรลดา สนามเสือป่า ให้คณาจารย์ฟังครับ
5/23/2018
ผศ. ดร. อานนท์ ศักดิ์วรวิชญ์
Word segmentation using Deep Learning (Deep cut) บรรยายโดย Rakpong Kittinaradorn จาก True Corporation ในงาน the second business analytics and data science contest/conference
Visualizing for real impact โดยอาจารย์ ดร. อานนท์ ศักดิ์วรวิชญ์ ผู้อำนวยการศูนย์คลังปัญญาและสารสนเทศ สถาบันบัณฑิตพัฒนบริหารศาสตร์ สาขาวิชา Business Analytics and Intelligence และสาขาวิทยาการประกันภัยและการบริหารความเสี่ยง สถาบันบัณฑิตพัฒนบริหารศาสตร์ บรรยายในงาน The 4th Data Cube Conference (Data Analytic to Real Application) เมื่อวันที่ clock
Saturday, July 22 at 9 AM - 5 PM
https://www.facebook.com/events/193038667886326/
ขอบคุณ ดร เอกสิทธิ์ พัชรวงศ์ศักดาที่เชิญไปบรรยายครับ สไลด์ชุดนี้มีคนถามหากันมากเลย post ให้ทุกคนครับ
Second prize business plan @ the First NIDA business analytics and data scien...BAINIDA
Second prize business plan @ the First NIDA business analytics and data sciences contest
ผู้ที่ได้รางวัลรองชนะเลิศอันดับ 1
1.นางสาวทอฝัน แหล๊ะตี สาขาประกันภัย
2.นางสาวผัลย์สุภา ศิริวงศ์นภา สาขาไอที
3.นางสาวนรีรัตน์ ตรีชีวันนาถ สาขาสถิติ
จากจุฬาลงกรณ์มหาวิทยาลัย คณะพาณิชยศาสตร์และการบัญชี
Second prize data analysis @ the First NIDA business analytics and data scie...BAINIDA
Second prize data analysis
@ the First NIDA business analytics and data sciences contest
1.นางสาวทอฝัน แหล๊ะตี สาขาประกันภัย
2.นางสาวผัลย์สุภา ศิริวงศ์นภา สาขาไอที
3.นางสาวนรีรัตน์ ตรีชีวันนาถ สาขาสถิติ
จาก คณะพาณิชยศาสตร์และการบัญชี จุฬาลงกรณ์มหาวิทยาลัย
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Instructions for Submissions thorugh G- Classroom.pptxJheel Barad
This presentation provides a briefing on how to upload submissions and documents in Google Classroom. It was prepared as part of an orientation for new Sainik School in-service teacher trainees. As a training officer, my goal is to ensure that you are comfortable and proficient with this essential tool for managing assignments and fostering student engagement.
We all have good and bad thoughts from time to time and situation to situation. We are bombarded daily with spiraling thoughts(both negative and positive) creating all-consuming feel , making us difficult to manage with associated suffering. Good thoughts are like our Mob Signal (Positive thought) amidst noise(negative thought) in the atmosphere. Negative thoughts like noise outweigh positive thoughts. These thoughts often create unwanted confusion, trouble, stress and frustration in our mind as well as chaos in our physical world. Negative thoughts are also known as “distorted thinking”.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
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Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
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1. The First NIDA Business Analytics and Data Sciences Contest/Conference
วันที่ 1-2 กันยายน 2559 ณ อาคารนวมินทราธิราช สถาบันบัณฑิตพัฒนบริหารศาสตร์
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-ผลเลือกตั้งจะออกมาเป็นเช่นไร หากรัฐธรรมนูญผ่าน
-ทานายผลการเลือกตั้งด้วย Data Sciences ได้หรือไม่
-ปัจจัยด้านสังคมเศรษฐกิจ ภูมิศาสตร์ ประชากรศาสตร์
พฤติกรรมศาสตร์ ปัจจัยใดที่ทานายผลการเลือกตั้งได้ดี
-พื้นที่เขตเลือกตั้งแบบใดมีแนวโน้มที่จะมีบัตรเสีย
Vote No และ No Vote เพื่อไทย หรือประชาธิปัตย์
-แบบจาลองแบบไหนที่ใช้ทานายผลเลือกตั้ง สร้างได้อย่างไร
Spatial regression model predicting Thailand’s election
อาจารย์ ดร. อานนท์ ศักดิ์วรวิชญ์
นางสาวรัชนีพร จันทร์สา คณะสถิติประยุกต์ NIDA
นวมินทราธิราช 4001 วันที่ 2 กันยายน 2559 13.30-14.00 น.
2. Spatial regression model predicting
Thailand’s election result.
Arnond Sakworawich, Ph.D.
Ratchaneeporn Jansa
Graduate School of Applied Statistics
National Institute of Development Administration, Bangkok, Thailand
3. Abstract
The purpose of the current research are to 1) investigate the spatial relationships of voting
behaviors among each electorates, 2) investigate geographical, behavioral, socio-economic, and
demographic components related to election results, and 3) build up the spatial negative binomial
regression models predicting Thailand election results. Election results in 2005 and 2007 retrieved
from Election Commission of Thailand (ECT) were used to predict % vote for no vote, vote No, voided
ballot, as well as % vote for Democrat Party, Pheu Thai Party, Chartthaipattana Party, and Bhumjaithai
Party as behavioral components for 2011 election results. Socio-economic and demographic variables
were from socio-economic status survey in 2010 from National statistical office. Geographic variables
were from department of land development and department of royal irrigation. Moran’s I statistics and
the spatial negative binomial regression model were used to investigate the spatial autocorrelation of
election results among electorates and the relationship between geographical, behavioral, socio-
economic, and demographic components and election results. This current research will shed light on
how to develop Thailand’s politics and it can also be applied for election and campaign management.
The spatial negative binomial regression model can be used to predict an incoming election results by
substitute 2011 election results with the near future election poll.
Keyword: Election, Spatial Model, geography, social, economics, demography, behavior
15. Attachai Ueranantasun, (2012). Analyzing National Elections of Thailand in 2005, 2007, and 2011 –
Graphical Approach. International Journal of Business and Social Science Vol. 3 No. 19
16. Objective
1)To investigate the spatial relationships of voting behaviors
among each election district.
2)To investigate geographical, behavioral, socio-economic, and
demographic components related to election results.
3)To build up the spatial regression models predicting Thailand
election results.
17. Demographic
- % Male, %Female
- Average Age
- Age Standard Deviation
- %Religion
- Population Density
Socio-economic components
-Average monthly Income per capita
-Poverty Rate
-Gini coefficient of monthly income
-Average monthly expenditures per capita
-Gini coefficient of monthly expenditures
-%Occupation Category
-%Type of business
-Work Status Category
-Education Level
Geographic
- Land Use
% of Urban and Built-up land
% of Agricultural land
% of Forest land
% of Water Body
% of Miscellaneous land
- % of Irrigation Area
- Region
Spatial Autocorrelation
- Moran’s I
% of Voting (2011)
- % of PeauThai
- % of Democrat
- % of Chat Thai Pat
- % of Poom Jai Thai
- % of Vote No
- % of No Vote
- % of Voided ballots
% of Voting (2005,2007)
% TRT 2005
% Democrat 2005
% ChatThai 2005
% MaHaChon 2005
% Other Party 2005
% PPP 2007
% Democratic 2007
% Chatthai 2007
% Pueapandin 2007
% Ruamjaithai Chatpattana
2007
% Matchimathipahai 2007
- % of Vote No
- % of No Vote
- % of Voided ballots
18. Source of data
• Office of the Election Commission of Thailand
• National Statistical Office Thailand
• Land Development Department
• Royal Irrigation Department
20. Party
2550
Total
Electorat
e Party list
PPP 199 34 233
Democrats 132 33 165
ChatThai 33 4 37
PueaPanDin 17 7 24
RuamJaiThaiChatPattana 8 1 9
MatchimmaThipaThai 7 0 7
PraChaRat 4 1 5
Total 400 80 480
National Election of Thailand in 2550
Electorate Party list
21. Party
2554
TotalElectorate Party list
PueaThai 204 61 265
Democrats 115 44 159
PhumJaiThai 29 5 34
ChatThaiPattana 15 4 19
ChatPattana
PueaPanDin 5 2 7
PalungChon 6 1 7
RukPraThesThai 0 4 4
MaTuPhum 1 1 2
RukSanti 0 1 1
Mahachon 0 1 1
PrachathipathaiMai 0 1 1
Total 375 125 500
National Election of Thailand in 2554
Electorate Party list
22. "Everything is related to everything else, but near things are more
related than distant things.”
Tobler W., (1970) "A computer movie simulating urban growth
in the Detroit region". Economic Geography, 46(2): 234-240.
Geographer Waldo R. Tobler’s stated in the first law of geography:
23. Spatial Autocorrelation
Geographer Waldo R. Tobler’s stated in the first law of geography:
"Everything is related to everything else, but near
things are more related than distant things.”
Source:
http://resources.arcgis.com/en/help/main/10.1
/index.html#//005p00000006000000
24. PueaThai Vote Share in 2554 (Electorate)
Moran's I for PueaThai Vote Share in 2011 (Moran’ s I =0.7287)
Local Spatial Autocorrelation (LISA) for PueaThai Vote
Share in 2011
25. Democrat Vote Share in 2554 (Electorate)
Moran's I for Democrats Vote Share in 2011 (Moran’ s I =0.7864)
Local Spatial Autocorrelation (LISA) for Democrats Vote
Share in 2011
26. ChatThaiPhatThana Vote Share in 2554 (Electorate)
Moran's I for ChatThaiPhattana Vote Share in 2011 (Moran’ s I =0.2822)
Local Spatial Autocorrelation (LISA) for ChatThaiPhattana
Vote Share in 2011
27. PhumJaiThai Vote Share in 2554 (Electorate)
Moran's I for PhumJaiThai Vote Share in 2011 (Moran’ s I =0.3482)
Local Spatial Autocorrelation (LISA) for PhumJaiThai
Vote Share in 2011
28. PueaThai Vote Share in 2554 (Party List)
Moran's I for PueaThai Vote Share in 2011
(Moran’ s I =0.8786)
Local Spatial Autocorrelation (LISA) for PueaThai Vote
Share in 2011
29. Democrat Vote Share in 2554 (Party List)
Moran's I for Democrats Vote Share in 2011
(Moran’ s I =0.8803)
Local Spatial Autocorrelation (LISA) for Democrats Vote
Share in 2011
30. ChatThaiPhatThana Vote Share in 2554(Party List)
Moran's I for ChatThaiPhattana Vote Share in
2011 (Moran’ s I =0.24872)
Local Spatial Autocorrelation (LISA) for ChatThaiPhattana
Vote Share in 2011
31. PhumJaiThai Vote Share in 2554 (Party List)
Moran's I for PhumJaiThai Vote Share in 2011
(Moran’ s I =0.5391)
Local Spatial Autocorrelation (LISA) for PhumJaiThai
Vote Share in 2011
32. Demography M SD
%PT54
%Dem54
%PJT54
%CTP54
%Other
Party54
%Voided
Ballot54
%VoteNo54
%Novote
54
Density/Square km 832.29 1995.40 -.05 .22 -.20 -.12 -.07 -.59 .55 .24
PrctFemale 50.75 1.22 -.09 .21 -.17 .01 -.14 -.51 .46 -.17
% Buddhist 94.30 16.50 .36 -.22 .06 -.03 -.15 -.03 -.03 .17
% Islam 5.10 16.46 -.37 .22 -.05 .03 .16 .03 .01 -.18
% Population age less than 15
years
20.80 5.14 -.04 -.11 .16 .03 .13 .38 -.43 .28
Average age 36.75 3.24 .18 -.16 .01 .12 -.10 .17 -.07 -.19
Age Standard Deviation 21.24 1.53 .08 -.26 .23 .15 .03 .56 -.50 .11
43. Y = β0 + λ WY + Xβ + ε
Y = β0 + Xβ + ρWε + ξ
ξ is “white noise”
Spatial Lag Regression Model Spatial Error Regression Model
residuals in neighboring locations (Wε)
OLS SPATIAL LAG SPATIAL ERROR
Baller, R., L. Anselin, S. Messner, G. Deane and D. Hawkins. 2001. Structural covariates of US
County homicide rates: incorporating spatial effects,. Criminology , 39, 561-590
49. Variable Coefficient SE z-value p-value
Constant 2.44 0.83 2.93 .003
% Contributing family worker -0.04 0.01 -3.54 .000
% work in agriculture sector 0.04 0.00 7.78 .000
Age Standard Deviation 0.09 0.03 2.82 .005
Average total expenditures 0.00 0.00 -7.31 .000
%Voided Ballot 48 0.44 0.05 8.22 .000
%Voided Ballot 50 0.16 0.04 3.62 .000
Lambda 0.65 0.05 12.69 .000
R-squared 0.85
-2LL 753.82
AIC 767.82
BIC 795.31
2554
50. Variable Coefficient SE z-value p-value
Constant 5.43 0.86 6.28 .000
Northeast region -1.10 0.42 -2.63 .009
North region -1.27 0.60 -2.12 .034
% No Vote 48 0.51 0.03 16.20 .000
% No Vote 50 0.24 0.03 7.39 .000
Lambda 0.46 0.07 6.95 .000
R-squared 0.80
-2LL 1586.5
AIC 1596.51
BIC 1616.14
2554
51. -Spatial autocorrelation cannot be ignored when we want to study election in Thailand.
- Spatial autocorrelation for PhueThai party is way higher than Democrat party.
- Spatial autocorrelation for party list is way higher than Electorate.
- Regionalism strongly influences election results.
-Socio-economic, demographic, geographic, and past behavioral factors are related to voting
behaviors.
- Past voting behaviors is the best predictor of future voting result.
- It is harder to predict voting result for small and medium sized political party.
- Urban, city, middle income, educated, working profession, and females tend to Vote NO.
- Low income, work in agricultural sector, without contributing family business tend to have VOIDED
ballots.
- Northerners and Northeasterners tends to participate in election more than other regions.
- Two large party is majority of Party list Voting.
Conclusion and Discussion
52. -Spatial regression models predicting party list voting result
- Develop model to predict future voting result when public election polls is available.
- Political development and socio-economic development
Future Research
53. The 2010 Household Socio-Economic Survey Whole Kingdom.
National Statistical Office (NSO)
• Area Survey: Whole Kingdom (both municipal and non-municipal areas)
• Duration: January to December, 2010
• Sample: 52,000 Households