Test for Normality Using a Characterization

1975 ◽  
pp. 91-104 ◽  
Author(s):  
Kendall McDonald ◽  
S. K. Katti
Keyword(s):  
Test For Normality

A Diagnostic Test for Normality within the Power Exponential Family

1986 ◽  
Vol 4 (3) ◽  
pp. 359 ◽  
Author(s):  
Dale J. Poirier ◽  
Mario D. Tello ◽  
Stanley E. Zin
Keyword(s):  
Diagnostic Test ◽  
Exponential Family ◽  
Test For Normality

scholarly journals PENGARUH LINGKUNGAN KELUARGA DAN SEKOLAH TERHADAP PERILAKU SISWA

2017 ◽  
Vol 1 (1) ◽  
pp. 52-58
Author(s):  
Andi Ridha S ◽  
St. Rajiah Rusydi
Keyword(s):  
Data Analysis ◽  
Linear Regression ◽  
Family Environment ◽  
School Environment ◽  
Student Behavior ◽  
Cluster Sampling ◽  
Reliability Test ◽  
Simple Linear Regression ◽  
R Value ◽  
Test For Normality

Tujuan penelitian ini adalah untuk mengetahui pengaruh lingkungan keluarga dan sekolah terhadap perilaku siswa di SMA Hang Tuah Makassar. Jenis penelitian yang digunakan bersifat deskriftif kuantitatif, yang beralokasi di SMA Hang Tuah Makassar.Teknik pengambilan sampel yaitu teknik Cluster/ judgmental  sebanyak 61 siswa. Teknik pengumpulan data melalui observasi, koesioner, wawancara, dan dokumentasi. Analisis data dengan langkah-langkah berupa validitas, realibilitas, uji normalitas, linearitas dan uji hipotesis dengan menggunakan rumus regresi linier sederhana dengan SPSS 17 for Windows. Berdasarkan hasil analisis data yang dilakukan, maka nilai signifikansi yang diperoleh 0,000, sedangkan nilai r square menunjukkan 0,58 artinya terdapat pengaruh lingkungan keluarga dan sekolah terhadap perilaku siswa di SMA Hang Tuah Makassar sebesar 58%.Kata Kunci: Lingkungan keluarga, lingkungan sekolah, perilaku siswa.The purpose of this study was to determine the influence of family and school environment on student behavior in SMA Hang Tuah Makassar. This type of research is descriptive quantitative, which located in SMA Hang Tuah Makassar. Cluster sampling is the technique / judgmental as many as 61 students. The technique of collecting data is through observation, questioner, interview, and documentation. Analysis of data by measures such as validity, reliability, test for normality, linearity and hypothesis testing using simple linear regression formula with SPSS 17 for Windows. Based on the results of the data analysis, the significant value gained 0,000, while the r value of 0.58 means that there are square shows the influence of family and school environment on student behavior in SMA Hang Tuah Makassar by 58%. Keywords: family environment, school environment, student behavior

On the Kuiper test for normality with mean and variance unknown

1970 ◽  
Vol 24 (2) ◽  
pp. 83-87 ◽  
Author(s):  
A. S. Louter ◽  
J. Koerts
Keyword(s):  
Mean And Variance ◽  
Kuiper Test ◽  
Test For Normality

scholarly journals Omnibus test for normality based on the Edgeworth expansion

PLoS ONE ◽  
2020 ◽  
Vol 15 (6) ◽  
pp. e0233901 ◽  
Author(s):  
Agnieszka Wyłomańska ◽  
D. Robert Iskander ◽  
Krzysztof Burnecki
Keyword(s):  
Edgeworth Expansion ◽  
Omnibus Test ◽  
Test For Normality

A NEW CHARACTERIZATION OF THE NORMAL DISTRIBUTION AND TEST FOR NORMALITY

2015 ◽  
Vol 32 (5) ◽  
pp. 1216-1252 ◽  
Author(s):  
Anil K. Bera ◽  
Antonio F. Galvao ◽  
Liang Wang ◽  
Zhijie Xiao
Keyword(s):  
Normal Distribution ◽  
Testing Procedure ◽  
Finite Sample ◽  
Omnibus Test ◽  
Sample Mean ◽  
Underlying Distribution ◽  
Asymptotic Covariance ◽  
Finite Sample Properties ◽  
Test For Normality

We study the asymptotic covariance function of the sample mean and quantile, and derive a new and surprising characterization of the normal distribution: the asymptotic covariance between the sample mean and quantile is constant across all quantiles,if and only ifthe underlying distribution is normal. This is a powerful result and facilitates statistical inference. Utilizing this result, we develop a new omnibus test for normality based on the quantile-mean covariance process. Compared to existing normality tests, the proposed testing procedure has several important attractive features. Monte Carlo evidence shows that the proposed test possesses good finite sample properties. In addition to the formal test, we suggest a graphical procedure that is easy to implement and visualize in practice. Finally, we illustrate the use of the suggested techniques with an application to stock return datasets.

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