Budi Pratikno
Department of Mathematics, Jenderal Soedirman University

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POWER OF THE TESTS DENGAN NON-SAMPLE PRIOR INFORMATION PADA PENGUJIAN HIPOTESIS SATU ARAH Budi Pratikno; Lina Sulistia; Yuliatri Wirawidya Haryono
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 8 No 2 (2016): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2016.8.2.2892

Abstract

The research discussed power of the tests with non-sample prior information (NSPI) in testing intercept on one-side-hypothesis. The testing is condcuted on a simple regression model (SRM) and multivariate simple regression model (MSRM), and the power of the tests are unrestricted test (UT), restricted test (RT), and preliminary-test test (PTT). The method for choosing the best tests is a maximum power and minimum size. A simulation study and graphical analysis are given using generate and real data. The result showed that the power of the test of the PTT are an alternative choice among the tests on both SRM and MSRM.
REGRESI LINEAR BIVARIAT SIMPEL DAN APLIKASINYA PADA DATA CUACA DI CILACAP Saniyah Saniyah; Budi Pratikno
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 6 No 1 (2014): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2014.6.1.2902

Abstract

This study discusses the simple bivariate linear regression on weather data in Cilacap district. This simple bivariate linear regression using the two response variables, rainfall () and humidity of an area (), and one predictor variable, the air temperature (). Regression model test method is a Wilk's Lamda test, the value of Wilk's Lamda = 0.881101 less than lambda table 0.903. The results show that the model and the both parameters are significant, with mean deviation error model is .
POWER AND SIZE OF NORMAL DISTRIBUTION AND ITS APPLICATIONS Budi Pratikno; Jajang Jajang; Setianingsih Setianingsih; Raden Sudarwo
Jurnal Ilmiah Matematika dan Pendidikan Matematika Vol 9 No 2 (2017): Jurnal Ilmiah Matematika dan Pendidikan Matematika
Publisher : Jurusan Matematika FMIPA Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2017.9.2.2871

Abstract

. The research studied power and size of normal distribution and its applications on linear regression model. The power and size formulas are derived, and the unrestricted test (UT), restrcited test (RT) and pre-test test (PTT) are used. The recommendation of the test is given by choosing maximum power and minimum size, and also graphical analysis. The result showed that the power and size for large standard deviation () tend to be identical and flat. In simulation study, the graphs of the UT, RT, and PTT are still similar to the previous research (Pratikno, 2012), where the PTT tend to lie between UT and RT.
POWER AND SIZE OF NORMAL DISTRIBUTION AND ITS APPLICATIONS Budi Pratikno; Jajang Jajang; Setianingsih Setianingsih; Raden Sudarwo
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 9 No 2 (2017): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2017.9.2.2871

Abstract

. The research studied power and size of normal distribution and its applications on linear regression model. The power and size formulas are derived, and the unrestricted test (UT), restrcited test (RT) and pre-test test (PTT) are used. The recommendation of the test is given by choosing maximum power and minimum size, and also graphical analysis. The result showed that the power and size for large standard deviation () tend to be identical and flat. In simulation study, the graphs of the UT, RT, and PTT are still similar to the previous research (Pratikno, 2012), where the PTT tend to lie between UT and RT.
POWER OF THE TESTS DENGAN NON-SAMPLE PRIOR INFORMATION PADA PENGUJIAN HIPOTESIS SATU ARAH Budi Pratikno; Lina Sulistia; Yuliatri Wirawidya Haryono
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 8 No 2 (2016): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2016.8.2.2892

Abstract

The research discussed power of the tests with non-sample prior information (NSPI) in testing intercept on one-side-hypothesis. The testing is condcuted on a simple regression model (SRM) and multivariate simple regression model (MSRM), and the power of the tests are unrestricted test (UT), restricted test (RT), and preliminary-test test (PTT). The method for choosing the best tests is a maximum power and minimum size. A simulation study and graphical analysis are given using generate and real data. The result showed that the power of the test of the PTT are an alternative choice among the tests on both SRM and MSRM.
REGRESI LINEAR BIVARIAT SIMPEL DAN APLIKASINYA PADA DATA CUACA DI CILACAP Saniyah Saniyah; Budi Pratikno
Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) Vol 6 No 1 (2014): Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP)
Publisher : Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20884/1.jmp.2014.6.1.2902

Abstract

This study discusses the simple bivariate linear regression on weather data in Cilacap district. This simple bivariate linear regression using the two response variables, rainfall () and humidity of an area (), and one predictor variable, the air temperature (). Regression model test method is a Wilk's Lamda test, the value of Wilk's Lamda = 0.881101 less than lambda table 0.903. The results show that the model and the both parameters are significant, with mean deviation error model is .