SlideShare une entreprise Scribd logo
1  sur  16
Télécharger pour lire hors ligne
Ordinal Logistic Regression
on New Integration Education Plan Takaful

Asaad, Al-Ahmadgaid B.
alstated@gmail.com
alstat.blogspot.com

MINDANAO STATE UNIVERSITY
ILIGAN INSTITUTE OF TECHNOLOGY
Introduction
Insurance is a form of risk management used to minimize loss or risk
against the risk of a contingent, uncertain loss (1). In Islam, there
is this called Takaful (Islamic Insurance). The central idea of Takaful
(Islamic insurance) contract is that it is a financial transaction of a
mutual co-operation between two parties to protect one of them from
unexpected future material risk.

2 of 16
Introduction
There are many Family Takaful Companies in Malaysia such as Syarikat
Takaful Malaysia, Etiqa Takaful, Ikhlas and others. The businesses
in takaful used the takaful operator as the administrator of the fund
and manages the fund in trust on behalf of the participants, and the
contract between the participants and the operator is governed under
the contract of Mudharabah (profit-sharing) or Wakalah (agency).

3 of 16
Definition of Terms
• Riders - A provision of an insurance policy that is purchased sepa-

rately from the basic policy and that provides additional benefits at
additional cost. Standard policies usually leave little room for modification or customization, beyond choosing deductibles and coverage
amounts. (4)
• Surrender Value - It is the amount the policyholder will get from

the life insurance company if he decides to exit the policy before
maturity. (5)
• Maturity Value - The amount to be paid to the holder of a financial

obligation at the obligation’s maturity. (6)

4 of 16
Proposed Model
The proposed model of new product of education plan has to combine
all the riders in one plan and the name be changed to Economic Education Plan Takaful. The rider should include health, accident, hospital
costs, loss an effort to work, critical illnesses, education, death benefit,
death coverage and also pension. Life insurance or family takaful is
needed for everyone in the modern, so the product must affordable to
every category of income earners.

5 of 16
Objectives of the Study
This paper exposes the study of Wan Muhamad Amir W. Ahmad et
al on the application of the Ordinary Logistic Regression Model for a
New Intergration Education Plan Takaful. This paper aims to:
• present the Ordinal Logistic Regression Analysis of the new propose

model;
• present the Correlation Analysis between items of the questionnaire

used in the study; and
• Investigate the association between the capabilities of buying takaful

insurance with other related predictors.

6 of 16
Significance of the Study
This paper will be useful to statisticians and researchers as it addresses
issues such as the global concept and interpretation of ordinal logistic
regression model, which were applied on the New Intergration Education Plan Takaful.

7 of 16
Scope and Limitation
This paper is an expository that focuses on the analysis of Ordinary
Logistic Regression Model applied in the New Integration Education
Plan Takaful on the article by Wan Muhamad Amir W. Ahmad et al.
There will be no programming or any statistical software to be used
in this paper. The author will only based on the results of the articles
published by Wan Muhamad Amir W. Ahmad et al.

8 of 16
Methodology
The researcher used questionnaire, containing 10 questions which cover
the age, status, level of education, types of jobs, monthly salary, the
number of children in the household, the cost of the new product in
education plan takaful, and etc. The required sample size was 385, but
the researchers used 410 respondents. Reliability in the questionnaire
studies were also tested repeatedly. In addition, the researchers used
Ordinal Logistic Regression to investigate the association between the
capabilities of buying takaful insurance with other related predictors.

9 of 16
Questionnaire
Questionnaire answered by 410 respondents.

10 of 16
Results and Discussion
The data were considered to be ordinal since some of the predictors
are ordinal. Below is the Correlation Analysis between items of the
questionnaire used.

11 of 16
Results and Discussion
Ordinal Logistic Regression Analysis

12 of 16
Conclusion
After interviewing the 400 respondents using the questionnaire, almost
all the respondents agreed that the integration model of education plan
takaful could attract all categories of income earners into buying it. The
most attractive aspect about this model, the plan offers affordable price
for all categories of income earners and it also includes almost complete
riders. This research has proved that the new idea of integration model
in education plan takaful has been accepted by all categories of income
earners.

13 of 16
Recommendations
This expository was only dependent on the results obtained by Wan
Muhamad Amir W. Ahmad et al. Due to that, we recommend using software for confirmation of the computations, and any possible
graphical illustration.

14 of 16
References
• (1) Insurance. Wikipedia. Retrieved October 10, 2012, from:

http://en.wikipedia.org/wiki/Insurance
• (2) Ahmad , W.M.A. W. et al (2012). Ordinal Logistic Regression

Model for a New Intergration Education Plan Takaful . European
Journal of Scientific Research . Vol.71 No.1 (2012), pp. 109-116
• (3) Rider. The Free Dictionary. Retrieved October 10, 2012, from:

http://financial-dictionary.thefreedictionary.com/Rider
• (4) Rider. Investopedia. Retrieved October 10, 2012, from:

http://www.investopedia.com/terms/r/
rider.asp#axzz28tkck3kE

15 of 16
References
• (5) ”What is Surrender Value?”. The Economic Times. Retrieved

October 10, 2012, from:
http://articles.economictimes.indiatimes.com/2009-12-09/
news/28435556_1_surrender-value-policy-premium
• (6) Maturity Value. The Free Dictionary. Retreived October 10,

2012, from:
http://financial-dictionary.thefreedictionary.com/
maturity+value

16 of 16

Contenu connexe

Tendances

Simple linear regression
Simple linear regressionSimple linear regression
Simple linear regressionpankaj8108
 
Correlation & Regression Analysis using SPSS
Correlation & Regression Analysis  using SPSSCorrelation & Regression Analysis  using SPSS
Correlation & Regression Analysis using SPSSParag Shah
 
Introduction to Generalized Linear Models
Introduction to Generalized Linear ModelsIntroduction to Generalized Linear Models
Introduction to Generalized Linear Modelsrichardchandler
 
Multiple Regression and Logistic Regression
Multiple Regression and Logistic RegressionMultiple Regression and Logistic Regression
Multiple Regression and Logistic RegressionKaushik Rajan
 
Non parametric methods
Non parametric methodsNon parametric methods
Non parametric methodsPedro Moreira
 
Bernoullis Random Variables And Binomial Distribution
Bernoullis Random Variables And Binomial DistributionBernoullis Random Variables And Binomial Distribution
Bernoullis Random Variables And Binomial Distributionmathscontent
 
Basic Descriptive statistics
Basic Descriptive statisticsBasic Descriptive statistics
Basic Descriptive statisticsAjendra Sharma
 
Ml3 logistic regression-and_classification_error_metrics
Ml3 logistic regression-and_classification_error_metricsMl3 logistic regression-and_classification_error_metrics
Ml3 logistic regression-and_classification_error_metricsankit_ppt
 
Statistics-Regression analysis
Statistics-Regression analysisStatistics-Regression analysis
Statistics-Regression analysisRabin BK
 
Correlation and Regression ppt
Correlation and Regression pptCorrelation and Regression ppt
Correlation and Regression pptSantosh Bhaskar
 
Logistic regression with SPSS examples
Logistic regression with SPSS examplesLogistic regression with SPSS examples
Logistic regression with SPSS examplesGaurav Kamboj
 
Inferential Statistics
Inferential StatisticsInferential Statistics
Inferential Statisticsewhite00
 
multiple regression
multiple regressionmultiple regression
multiple regressionPriya Sharma
 
Presentation On Regression
Presentation On RegressionPresentation On Regression
Presentation On Regressionalok tiwari
 
Regression Analysis - Thiyagu
Regression Analysis - ThiyaguRegression Analysis - Thiyagu
Regression Analysis - ThiyaguThiyagu K
 
Statistics "Descriptive & Inferential"
Statistics "Descriptive & Inferential"Statistics "Descriptive & Inferential"
Statistics "Descriptive & Inferential"Dalia El-Shafei
 

Tendances (20)

Simple linear regression
Simple linear regressionSimple linear regression
Simple linear regression
 
Correlation & Regression Analysis using SPSS
Correlation & Regression Analysis  using SPSSCorrelation & Regression Analysis  using SPSS
Correlation & Regression Analysis using SPSS
 
Introduction to Generalized Linear Models
Introduction to Generalized Linear ModelsIntroduction to Generalized Linear Models
Introduction to Generalized Linear Models
 
Regression analysis
Regression analysisRegression analysis
Regression analysis
 
Multiple Regression and Logistic Regression
Multiple Regression and Logistic RegressionMultiple Regression and Logistic Regression
Multiple Regression and Logistic Regression
 
Binary Logistic Regression
Binary Logistic RegressionBinary Logistic Regression
Binary Logistic Regression
 
Non parametric methods
Non parametric methodsNon parametric methods
Non parametric methods
 
Bernoullis Random Variables And Binomial Distribution
Bernoullis Random Variables And Binomial DistributionBernoullis Random Variables And Binomial Distribution
Bernoullis Random Variables And Binomial Distribution
 
Basic Descriptive statistics
Basic Descriptive statisticsBasic Descriptive statistics
Basic Descriptive statistics
 
Ml3 logistic regression-and_classification_error_metrics
Ml3 logistic regression-and_classification_error_metricsMl3 logistic regression-and_classification_error_metrics
Ml3 logistic regression-and_classification_error_metrics
 
Statistics-Regression analysis
Statistics-Regression analysisStatistics-Regression analysis
Statistics-Regression analysis
 
Correlation and Regression ppt
Correlation and Regression pptCorrelation and Regression ppt
Correlation and Regression ppt
 
Logistic regression with SPSS examples
Logistic regression with SPSS examplesLogistic regression with SPSS examples
Logistic regression with SPSS examples
 
Inferential Statistics
Inferential StatisticsInferential Statistics
Inferential Statistics
 
multiple regression
multiple regressionmultiple regression
multiple regression
 
Presentation On Regression
Presentation On RegressionPresentation On Regression
Presentation On Regression
 
Regression Analysis - Thiyagu
Regression Analysis - ThiyaguRegression Analysis - Thiyagu
Regression Analysis - Thiyagu
 
Testing Hypothesis
Testing HypothesisTesting Hypothesis
Testing Hypothesis
 
Statistics "Descriptive & Inferential"
Statistics "Descriptive & Inferential"Statistics "Descriptive & Inferential"
Statistics "Descriptive & Inferential"
 
Linear regression
Linear regression Linear regression
Linear regression
 

En vedette

Intro to Logistic Regression
Intro to Logistic RegressionIntro to Logistic Regression
Intro to Logistic RegressionJay Victoria
 
Logistic regression (blyth 2006) (simplified)
Logistic regression (blyth 2006) (simplified)Logistic regression (blyth 2006) (simplified)
Logistic regression (blyth 2006) (simplified)MikeBlyth
 
Logistic regression
Logistic regressionLogistic regression
Logistic regressionDrZahid Khan
 
Logistic regression
Logistic regressionLogistic regression
Logistic regressionsaba khan
 
Boosted Tree-based Multinomial Logit Model for Aggregated Market Data
Boosted Tree-based Multinomial Logit Model for Aggregated Market DataBoosted Tree-based Multinomial Logit Model for Aggregated Market Data
Boosted Tree-based Multinomial Logit Model for Aggregated Market DataJay (Jianqiang) Wang
 
Logistic Regression/Markov Chain presentation
Logistic Regression/Markov Chain presentationLogistic Regression/Markov Chain presentation
Logistic Regression/Markov Chain presentationMichael Hankin
 
Transparency7
Transparency7Transparency7
Transparency7A M
 
1.5.1 measures basic concepts
1.5.1 measures basic concepts1.5.1 measures basic concepts
1.5.1 measures basic conceptsA M
 
(마더세이프 라운드) Logistic regression
(마더세이프 라운드) Logistic regression(마더세이프 라운드) Logistic regression
(마더세이프 라운드) Logistic regressionmothersafe
 
Generalized Logistic Regression - by example (Anthony Kilili)
Generalized Logistic Regression - by example (Anthony Kilili)Generalized Logistic Regression - by example (Anthony Kilili)
Generalized Logistic Regression - by example (Anthony Kilili)Anthony Kilili
 
Mode Choice analysis for work trips using Multinomial Logit model for Windsor...
Mode Choice analysis for work trips using Multinomial Logit model for Windsor...Mode Choice analysis for work trips using Multinomial Logit model for Windsor...
Mode Choice analysis for work trips using Multinomial Logit model for Windsor...Aakash Bagchi
 
Logistic Regression: Behind the Scenes
Logistic Regression: Behind the ScenesLogistic Regression: Behind the Scenes
Logistic Regression: Behind the ScenesChris White
 
From logistic regression to linear chain CRF
From logistic regression to linear chain CRFFrom logistic regression to linear chain CRF
From logistic regression to linear chain CRFDarren Yow-Bang Wang
 
4.5. logistic regression
4.5. logistic regression4.5. logistic regression
4.5. logistic regressionA M
 
ESL 4.4.3-4.5: Logistic Reression (contd.) and Separating Hyperplane
ESL 4.4.3-4.5: Logistic Reression (contd.) and Separating HyperplaneESL 4.4.3-4.5: Logistic Reression (contd.) and Separating Hyperplane
ESL 4.4.3-4.5: Logistic Reression (contd.) and Separating HyperplaneShinichi Tamura
 

En vedette (20)

Intro to Logistic Regression
Intro to Logistic RegressionIntro to Logistic Regression
Intro to Logistic Regression
 
Logistic regression (blyth 2006) (simplified)
Logistic regression (blyth 2006) (simplified)Logistic regression (blyth 2006) (simplified)
Logistic regression (blyth 2006) (simplified)
 
Logistic regression
Logistic regressionLogistic regression
Logistic regression
 
Logistic Regression Analysis
Logistic Regression AnalysisLogistic Regression Analysis
Logistic Regression Analysis
 
Logistic regression
Logistic regressionLogistic regression
Logistic regression
 
Logistic regression
Logistic regressionLogistic regression
Logistic regression
 
MRA vs AVM
MRA vs AVM MRA vs AVM
MRA vs AVM
 
Boosted Tree-based Multinomial Logit Model for Aggregated Market Data
Boosted Tree-based Multinomial Logit Model for Aggregated Market DataBoosted Tree-based Multinomial Logit Model for Aggregated Market Data
Boosted Tree-based Multinomial Logit Model for Aggregated Market Data
 
Logistic Regression/Markov Chain presentation
Logistic Regression/Markov Chain presentationLogistic Regression/Markov Chain presentation
Logistic Regression/Markov Chain presentation
 
Transparency7
Transparency7Transparency7
Transparency7
 
1.5.1 measures basic concepts
1.5.1 measures basic concepts1.5.1 measures basic concepts
1.5.1 measures basic concepts
 
(마더세이프 라운드) Logistic regression
(마더세이프 라운드) Logistic regression(마더세이프 라운드) Logistic regression
(마더세이프 라운드) Logistic regression
 
Generalized Logistic Regression - by example (Anthony Kilili)
Generalized Logistic Regression - by example (Anthony Kilili)Generalized Logistic Regression - by example (Anthony Kilili)
Generalized Logistic Regression - by example (Anthony Kilili)
 
Mode Choice analysis for work trips using Multinomial Logit model for Windsor...
Mode Choice analysis for work trips using Multinomial Logit model for Windsor...Mode Choice analysis for work trips using Multinomial Logit model for Windsor...
Mode Choice analysis for work trips using Multinomial Logit model for Windsor...
 
Logistic Regression: Behind the Scenes
Logistic Regression: Behind the ScenesLogistic Regression: Behind the Scenes
Logistic Regression: Behind the Scenes
 
From logistic regression to linear chain CRF
From logistic regression to linear chain CRFFrom logistic regression to linear chain CRF
From logistic regression to linear chain CRF
 
Choice Models
Choice ModelsChoice Models
Choice Models
 
4.5. logistic regression
4.5. logistic regression4.5. logistic regression
4.5. logistic regression
 
Binary Logistic Regression Example
Binary Logistic Regression ExampleBinary Logistic Regression Example
Binary Logistic Regression Example
 
ESL 4.4.3-4.5: Logistic Reression (contd.) and Separating Hyperplane
ESL 4.4.3-4.5: Logistic Reression (contd.) and Separating HyperplaneESL 4.4.3-4.5: Logistic Reression (contd.) and Separating Hyperplane
ESL 4.4.3-4.5: Logistic Reression (contd.) and Separating Hyperplane
 

Similaire à Ordinal Logistic Regression New Education Takaful Plan

Introduction to risk management & insurance
Introduction to risk management & insuranceIntroduction to risk management & insurance
Introduction to risk management & insuranceTonderayi Chikanda
 
paperpublished (1).pdf
paperpublished (1).pdfpaperpublished (1).pdf
paperpublished (1).pdfvishalp47
 
Research proposal on insurance
Research proposal on insuranceResearch proposal on insurance
Research proposal on insuranceRavi Pandya
 
RASHMITA MANONDDRA BLACK BOOK.docx
RASHMITA MANONDDRA BLACK BOOK.docxRASHMITA MANONDDRA BLACK BOOK.docx
RASHMITA MANONDDRA BLACK BOOK.docxLittleLap
 
Performence of mutual fund by. karan gujrati
Performence of mutual fund by. karan gujratiPerformence of mutual fund by. karan gujrati
Performence of mutual fund by. karan gujratiKaran Gujrati
 
Scoring and predicting risk preferences
Scoring and predicting risk preferencesScoring and predicting risk preferences
Scoring and predicting risk preferencesGurdal Ertek
 
Feasibility Study on Employer-Sponsored Small Dollar Loans
Feasibility Study on Employer-Sponsored Small Dollar LoansFeasibility Study on Employer-Sponsored Small Dollar Loans
Feasibility Study on Employer-Sponsored Small Dollar LoansBruno Gremez
 
9508612 bajaj-allianz 2
9508612 bajaj-allianz 29508612 bajaj-allianz 2
9508612 bajaj-allianz 2shivamravi
 
9508612 bajaj-allianz 2
9508612 bajaj-allianz 29508612 bajaj-allianz 2
9508612 bajaj-allianz 2shivamravi
 

Similaire à Ordinal Logistic Regression New Education Takaful Plan (20)

Recitation of Public and Private Sector General Insurance Industry in Structu...
Recitation of Public and Private Sector General Insurance Industry in Structu...Recitation of Public and Private Sector General Insurance Industry in Structu...
Recitation of Public and Private Sector General Insurance Industry in Structu...
 
Recitation of Public and Private Sector General Insurance Industry in Structu...
Recitation of Public and Private Sector General Insurance Industry in Structu...Recitation of Public and Private Sector General Insurance Industry in Structu...
Recitation of Public and Private Sector General Insurance Industry in Structu...
 
Empirical study on policyholder’s opinion towards reason of taking non-Life I...
Empirical study on policyholder’s opinion towards reason of taking non-Life I...Empirical study on policyholder’s opinion towards reason of taking non-Life I...
Empirical study on policyholder’s opinion towards reason of taking non-Life I...
 
Introduction to risk management & insurance
Introduction to risk management & insuranceIntroduction to risk management & insurance
Introduction to risk management & insurance
 
paperpublished (1).pdf
paperpublished (1).pdfpaperpublished (1).pdf
paperpublished (1).pdf
 
Policy Interventions to Contemporary Challenges and the Performance of Insura...
Policy Interventions to Contemporary Challenges and the Performance of Insura...Policy Interventions to Contemporary Challenges and the Performance of Insura...
Policy Interventions to Contemporary Challenges and the Performance of Insura...
 
Research proposal on insurance
Research proposal on insuranceResearch proposal on insurance
Research proposal on insurance
 
RASHMITA MANONDDRA BLACK BOOK.docx
RASHMITA MANONDDRA BLACK BOOK.docxRASHMITA MANONDDRA BLACK BOOK.docx
RASHMITA MANONDDRA BLACK BOOK.docx
 
Performence of mutual fund by. karan gujrati
Performence of mutual fund by. karan gujratiPerformence of mutual fund by. karan gujrati
Performence of mutual fund by. karan gujrati
 
Scoring and predicting risk preferences
Scoring and predicting risk preferencesScoring and predicting risk preferences
Scoring and predicting risk preferences
 
project
projectproject
project
 
Ijciet 10 02_079
Ijciet 10 02_079Ijciet 10 02_079
Ijciet 10 02_079
 
An Empirical Note General Insurance Products
An Empirical Note General Insurance ProductsAn Empirical Note General Insurance Products
An Empirical Note General Insurance Products
 
AN EMPIRICAL NOTE ON GENERAL INSURANCE PRODUCTS
AN EMPIRICAL NOTE ON GENERAL INSURANCE PRODUCTSAN EMPIRICAL NOTE ON GENERAL INSURANCE PRODUCTS
AN EMPIRICAL NOTE ON GENERAL INSURANCE PRODUCTS
 
Ijm 06 10_015
Ijm 06 10_015Ijm 06 10_015
Ijm 06 10_015
 
Ostraa - Overview
Ostraa - OverviewOstraa - Overview
Ostraa - Overview
 
Technological Acceptance and Consumer's Behavior on Buying Online Insurance
Technological Acceptance and Consumer's Behavior on Buying Online InsuranceTechnological Acceptance and Consumer's Behavior on Buying Online Insurance
Technological Acceptance and Consumer's Behavior on Buying Online Insurance
 
Feasibility Study on Employer-Sponsored Small Dollar Loans
Feasibility Study on Employer-Sponsored Small Dollar LoansFeasibility Study on Employer-Sponsored Small Dollar Loans
Feasibility Study on Employer-Sponsored Small Dollar Loans
 
9508612 bajaj-allianz 2
9508612 bajaj-allianz 29508612 bajaj-allianz 2
9508612 bajaj-allianz 2
 
9508612 bajaj-allianz 2
9508612 bajaj-allianz 29508612 bajaj-allianz 2
9508612 bajaj-allianz 2
 

Dernier

EMBODO Lesson Plan Grade 9 Law of Sines.docx
EMBODO Lesson Plan Grade 9 Law of Sines.docxEMBODO Lesson Plan Grade 9 Law of Sines.docx
EMBODO Lesson Plan Grade 9 Law of Sines.docxElton John Embodo
 
ROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxVanesaIglesias10
 
ClimART Action | eTwinning Project
ClimART Action    |    eTwinning ProjectClimART Action    |    eTwinning Project
ClimART Action | eTwinning Projectjordimapav
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfVanessa Camilleri
 
Measures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataMeasures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataBabyAnnMotar
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSJoshuaGantuangco2
 
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfVirtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfErwinPantujan2
 
Textual Evidence in Reading and Writing of SHS
Textual Evidence in Reading and Writing of SHSTextual Evidence in Reading and Writing of SHS
Textual Evidence in Reading and Writing of SHSMae Pangan
 
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...Postal Advocate Inc.
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptxmary850239
 
Choosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for ParentsChoosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for Parentsnavabharathschool99
 
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxINTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxHumphrey A Beña
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Celine George
 
Active Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfActive Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfPatidar M
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designMIPLM
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfJemuel Francisco
 
Dust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEDust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEaurabinda banchhor
 
Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Mark Reed
 

Dernier (20)

EMBODO Lesson Plan Grade 9 Law of Sines.docx
EMBODO Lesson Plan Grade 9 Law of Sines.docxEMBODO Lesson Plan Grade 9 Law of Sines.docx
EMBODO Lesson Plan Grade 9 Law of Sines.docx
 
ROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptxROLES IN A STAGE PRODUCTION in arts.pptx
ROLES IN A STAGE PRODUCTION in arts.pptx
 
ClimART Action | eTwinning Project
ClimART Action    |    eTwinning ProjectClimART Action    |    eTwinning Project
ClimART Action | eTwinning Project
 
ICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdfICS2208 Lecture6 Notes for SL spaces.pdf
ICS2208 Lecture6 Notes for SL spaces.pdf
 
Paradigm shift in nursing research by RS MEHTA
Paradigm shift in nursing research by RS MEHTAParadigm shift in nursing research by RS MEHTA
Paradigm shift in nursing research by RS MEHTA
 
Measures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped dataMeasures of Position DECILES for ungrouped data
Measures of Position DECILES for ungrouped data
 
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTSGRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
GRADE 4 - SUMMATIVE TEST QUARTER 4 ALL SUBJECTS
 
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdfVirtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
Virtual-Orientation-on-the-Administration-of-NATG12-NATG6-and-ELLNA.pdf
 
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptxYOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
YOUVE GOT EMAIL_FINALS_EL_DORADO_2024.pptx
 
Textual Evidence in Reading and Writing of SHS
Textual Evidence in Reading and Writing of SHSTextual Evidence in Reading and Writing of SHS
Textual Evidence in Reading and Writing of SHS
 
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
USPS® Forced Meter Migration - How to Know if Your Postage Meter Will Soon be...
 
4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx4.18.24 Movement Legacies, Reflection, and Review.pptx
4.18.24 Movement Legacies, Reflection, and Review.pptx
 
Choosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for ParentsChoosing the Right CBSE School A Comprehensive Guide for Parents
Choosing the Right CBSE School A Comprehensive Guide for Parents
 
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptxINTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
INTRODUCTION TO CATHOLIC CHRISTOLOGY.pptx
 
Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17Field Attribute Index Feature in Odoo 17
Field Attribute Index Feature in Odoo 17
 
Active Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdfActive Learning Strategies (in short ALS).pdf
Active Learning Strategies (in short ALS).pdf
 
Keynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-designKeynote by Prof. Wurzer at Nordex about IP-design
Keynote by Prof. Wurzer at Nordex about IP-design
 
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdfGrade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
Grade 9 Quarter 4 Dll Grade 9 Quarter 4 DLL.pdf
 
Dust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSEDust Of Snow By Robert Frost Class-X English CBSE
Dust Of Snow By Robert Frost Class-X English CBSE
 
Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)Influencing policy (training slides from Fast Track Impact)
Influencing policy (training slides from Fast Track Impact)
 

Ordinal Logistic Regression New Education Takaful Plan

  • 1. Ordinal Logistic Regression on New Integration Education Plan Takaful Asaad, Al-Ahmadgaid B. alstated@gmail.com alstat.blogspot.com MINDANAO STATE UNIVERSITY ILIGAN INSTITUTE OF TECHNOLOGY
  • 2. Introduction Insurance is a form of risk management used to minimize loss or risk against the risk of a contingent, uncertain loss (1). In Islam, there is this called Takaful (Islamic Insurance). The central idea of Takaful (Islamic insurance) contract is that it is a financial transaction of a mutual co-operation between two parties to protect one of them from unexpected future material risk. 2 of 16
  • 3. Introduction There are many Family Takaful Companies in Malaysia such as Syarikat Takaful Malaysia, Etiqa Takaful, Ikhlas and others. The businesses in takaful used the takaful operator as the administrator of the fund and manages the fund in trust on behalf of the participants, and the contract between the participants and the operator is governed under the contract of Mudharabah (profit-sharing) or Wakalah (agency). 3 of 16
  • 4. Definition of Terms • Riders - A provision of an insurance policy that is purchased sepa- rately from the basic policy and that provides additional benefits at additional cost. Standard policies usually leave little room for modification or customization, beyond choosing deductibles and coverage amounts. (4) • Surrender Value - It is the amount the policyholder will get from the life insurance company if he decides to exit the policy before maturity. (5) • Maturity Value - The amount to be paid to the holder of a financial obligation at the obligation’s maturity. (6) 4 of 16
  • 5. Proposed Model The proposed model of new product of education plan has to combine all the riders in one plan and the name be changed to Economic Education Plan Takaful. The rider should include health, accident, hospital costs, loss an effort to work, critical illnesses, education, death benefit, death coverage and also pension. Life insurance or family takaful is needed for everyone in the modern, so the product must affordable to every category of income earners. 5 of 16
  • 6. Objectives of the Study This paper exposes the study of Wan Muhamad Amir W. Ahmad et al on the application of the Ordinary Logistic Regression Model for a New Intergration Education Plan Takaful. This paper aims to: • present the Ordinal Logistic Regression Analysis of the new propose model; • present the Correlation Analysis between items of the questionnaire used in the study; and • Investigate the association between the capabilities of buying takaful insurance with other related predictors. 6 of 16
  • 7. Significance of the Study This paper will be useful to statisticians and researchers as it addresses issues such as the global concept and interpretation of ordinal logistic regression model, which were applied on the New Intergration Education Plan Takaful. 7 of 16
  • 8. Scope and Limitation This paper is an expository that focuses on the analysis of Ordinary Logistic Regression Model applied in the New Integration Education Plan Takaful on the article by Wan Muhamad Amir W. Ahmad et al. There will be no programming or any statistical software to be used in this paper. The author will only based on the results of the articles published by Wan Muhamad Amir W. Ahmad et al. 8 of 16
  • 9. Methodology The researcher used questionnaire, containing 10 questions which cover the age, status, level of education, types of jobs, monthly salary, the number of children in the household, the cost of the new product in education plan takaful, and etc. The required sample size was 385, but the researchers used 410 respondents. Reliability in the questionnaire studies were also tested repeatedly. In addition, the researchers used Ordinal Logistic Regression to investigate the association between the capabilities of buying takaful insurance with other related predictors. 9 of 16
  • 10. Questionnaire Questionnaire answered by 410 respondents. 10 of 16
  • 11. Results and Discussion The data were considered to be ordinal since some of the predictors are ordinal. Below is the Correlation Analysis between items of the questionnaire used. 11 of 16
  • 12. Results and Discussion Ordinal Logistic Regression Analysis 12 of 16
  • 13. Conclusion After interviewing the 400 respondents using the questionnaire, almost all the respondents agreed that the integration model of education plan takaful could attract all categories of income earners into buying it. The most attractive aspect about this model, the plan offers affordable price for all categories of income earners and it also includes almost complete riders. This research has proved that the new idea of integration model in education plan takaful has been accepted by all categories of income earners. 13 of 16
  • 14. Recommendations This expository was only dependent on the results obtained by Wan Muhamad Amir W. Ahmad et al. Due to that, we recommend using software for confirmation of the computations, and any possible graphical illustration. 14 of 16
  • 15. References • (1) Insurance. Wikipedia. Retrieved October 10, 2012, from: http://en.wikipedia.org/wiki/Insurance • (2) Ahmad , W.M.A. W. et al (2012). Ordinal Logistic Regression Model for a New Intergration Education Plan Takaful . European Journal of Scientific Research . Vol.71 No.1 (2012), pp. 109-116 • (3) Rider. The Free Dictionary. Retrieved October 10, 2012, from: http://financial-dictionary.thefreedictionary.com/Rider • (4) Rider. Investopedia. Retrieved October 10, 2012, from: http://www.investopedia.com/terms/r/ rider.asp#axzz28tkck3kE 15 of 16
  • 16. References • (5) ”What is Surrender Value?”. The Economic Times. Retrieved October 10, 2012, from: http://articles.economictimes.indiatimes.com/2009-12-09/ news/28435556_1_surrender-value-policy-premium • (6) Maturity Value. The Free Dictionary. Retreived October 10, 2012, from: http://financial-dictionary.thefreedictionary.com/ maturity+value 16 of 16