The t-test of a regression coefficient for imprecise data

Muhammad Aslam

Article Details

The t-test of a regression coefficient for imprecise data

Authors:

Muhammad Aslam

Publisher:

Hacettepe University

Main Topics:

Forensic Evaluation | Inference and Statistics | Large and Complex Data Theory | Soft Computing

Journal:

Hacettepe Journal of Mathematics and Statistics Vol.53 Issue 4, pp.1130-1140

Document Type:

Article

Publication Date:

8/2024

Document Language:

English

Document ID (Org No.):

2001325563

pISSN:

2651-477X

Keywords:

Abstract:

 The existing t-test for testing the significance of the regression coefficient is applied when cent percent observations of the data are precise, exact and certain. In practice, the measurement data or data recorded in an uncertain environment do not have all precise observations. The imprecise data cannot be analyzed using the existing t-test for testing the significance of the regression coefficient. In this paper, we will present the design of a t-test for testing the significance of the regression coefficient under neutrosophic statistics. The proposed t-test for testing the significance of the regression coefficient can be applied to imprecise data. The effect of the degree of uncertainty on the power of the test will be studied. The proposed t-test for testing the significance of the regression coefficient will be applied using the imprecise data. From the analysis, it is concluded that the proposed t-test for testing the significance of the regression coefficient will be informative, flexible and adequate to be applied to imprecise data.

 The existing t-test for testing the significance of the regression coefficient is applied when cent percent observations of the data are precise, exact and certain. In practice, the measurement data or data recorded in an uncertain environment do not have all precise observations. The imprecise data cannot be analyzed using the existing t-test for testing the significance of the regression coefficient. In this paper, we will present the design of a t-test for testing the significance of the regression coefficient under neutrosophic statistics. The proposed t-test for testing the significance of the regression coefficient can be applied to imprecise data. The effect of the degree of uncertainty on the power of the test will be studied. The proposed t-test for testing the significance of the regression coefficient will be applied using the imprecise data. From the analysis, it is concluded that the proposed t-test for testing the significance of the regression coefficient will be informative, flexible and adequate to be applied to imprecise data.

 The existing t-test for testing the significance of the regression coefficient is applied when cent percent observations of the data are precise, exact and certain. In practice, the measurement data or data recorded in an uncertain environment do not have all precise observations. The imprecise data cannot be analyzed using the existing t-test for testing the significance of the regression coefficient. In this paper, we will present the design of a t-test for testing the significance of the regression coefficient under neutrosophic statistics. The proposed t-test for testing the significance of the regression coefficient can be applied to imprecise data. The effect of the degree of uncertainty on the power of the test will be studied. The proposed t-test for testing the significance of the regression coefficient will be applied using the imprecise data. From the analysis, it is concluded that the proposed t-test for testing the significance of the regression coefficient will be informative, flexible and adequate to be applied to imprecise data.

 The existing t-test for testing the significance of the regression coefficient is applied when cent percent observations of the data are precise, exact and certain. In practice, the measurement data or data recorded in an uncertain environment do not have all precise observations. The imprecise data cannot be analyzed using the existing t-test for testing the significance of the regression coefficient. In this paper, we will present the design of a t-test for testing the significance of the regression coefficient under neutrosophic statistics. The proposed t-test for testing the significance of the regression coefficient can be applied to imprecise data. The effect of the degree of uncertainty on the power of the test will be studied. The proposed t-test for testing the significance of the regression coefficient will be applied using the imprecise data. From the analysis, it is concluded that the proposed t-test for testing the significance of the regression coefficient will be informative, flexible and adequate to be applied to imprecise data.

Article Details

The t-test of a regression coefficient for imprecise data

Authors:

Muhammad Aslam

Publisher:

Hacettepe University

Main Topics:

Forensic Evaluation | Inference and Statistics | Large and Complex Data Theory | Soft Computing

Journal:

Hacettepe Journal of Mathematics and Statistics Vol.53 Issue 4, pp.1130-1140

Document Type:

Article

Publication Date:

8/2024

Document Language:

English

Document ID (Org No.):

2001325563

pISSN:

2651-477X

t-test

inference

power of the test

simulation

level of significance

Issues

Article Details

The t-test of a regression coefficient for imprecise data

Authors: Muhammad Aslam

Publisher: Hacettepe University

Main Topics: Forensic Evaluation | Inference and Statistics | Large and Complex Data Theory | Soft Computing

Journal: Hacettepe Journal of Mathematics and Statistics Vol.53 Issue 4, pp.1130-1140

Document Type: Article

Publication Date: 8/2024

Document Language: English

Document ID (Org No.): 2001325563

pISSN: 2651-477X

t-test

inference

power of the test

simulation

level of significance

Issues

Authors:

Muhammad Aslam

Publisher:

Hacettepe University

Main Topics:

Forensic Evaluation | Inference and Statistics | Large and Complex Data Theory | Soft Computing

Journal:

Hacettepe Journal of Mathematics and Statistics Vol.53 Issue 4, pp.1130-1140

Document Type:

Article

Publication Date:

8/2024

Document Language:

English

Document ID (Org No.):

2001325563

pISSN:

2651-477X