COMPLEX ANALYSIS I
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Mohammad Momenzadeh was born in 1982, in the Tehran capital city of Iran. He completed his primary and high school education in American college(Alborz) . His education followed with an undergraduate degree at the Shiraz State University, Faculty of Art and science, Department of Mathematics (20002004) in pure mathematic. He followed Graduate degree at Urmiyeh State University (2006) in Harmonic Analysis presented thesis in title of "Multiplication Invariant Subspace of Bergman Space" and PhD (2016) at Eastern Mediterranean University, Department of Mathematics In Jan 2016. M. Momenzadeh presented his thesis titled Comprehensive study of qBernoulli qEuler and qGenocchi polynomials , and was awarded the title of Doctor of Mathematics (PHD). Momenzadeh worked as a Part time lecturer at the several university at Iran including Air force university (shahid sattari), many Branch of Azad University (south Tehran, east Tehran, Qazvin, Garmsar), Nonprofit university of ALLAMEH QAZVINI, at Iran between the years 20062010, as a Research Assistant at Eastern Mediterranean University (20102016), and as Part time lecturer at the same institute (2016). Momenzadeh published several papers in a title of his Phd thesis and Music and Mathematics. Since 20.11.2016, he has been working as a Doctor at Near East University. Mohammad Momenzadeh has 3 international articles and has attended 2 conferences.
Applied Mathematic and Computer Science
Eastern Mediterranean University
Harmonic Analysis
Urmiyeh State University
Pure Mathematic
Shiraz State University
The main purpose of this paper is to introduce and investigate a class of generalized Bernoulli polynomials and Euler polynomials based on the generating function. We unify all forms of q–exponential functions by one more parameter. We study some conditions on this parameter to related this to some classical results for qBernoulli numbers and polynomials.
Bu yazının asıl amacı, üretme fonksiyonuna dayalı olarak bir genelleştirilmiş Bernoulli polinomları ve Euler polinomları sınıfını tanıtmak ve araştırmaktır. Tüm q – üstel fonksiyonların biçimlerini bir parametre daha birleştiriyoruz. Bunu, qBernoulli sayıları ve polinomları için bazı klasik sonuçlarla ilişkilendirmek için bu parametrede bazı koşulları inceliyoruz.
We study the analogue of EulerMaclaurin formula and by introducing a new operator we drive to this form. Moreover, approximation properties of Bernoulli polynomials are discussed. We estimate the suitable functions as a combination of truncated series of Bernoulli polynomials and the error is calculated. This paper can be helpful in two different branches: first we solve the differential equations by estimating functions and second we may apply these techniques for operator theory.
EulerMaclaurin formülünün analogunu inceliyoruz ve bu forma süren yeniuygulayıcıyı tanıtarak. Ayrıca, Bernoulli polinomlarının yaklaşım özellikleri tartışılmıştır. Uygun fonksiyonları kesilmiş Bernoulli polinomları dizisinin bir kombinasyonu olarak tahmin ediyoruz ve hata hesaplanıyor. Bu makale iki farklı dalda yardımcı olabilir: önce diferansiyel denklemleri fonksiyonları tahmin ederek çözeriz, sonra da bu teknikleri operatör teorisi için kullanabiliriz.

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1.Identify and test assumptions for statistical tests. 2. Select, conduct and report appropriate statistics to test hypotheses with a) One independent variable and three or more levels (aka groups): ONEWAY ANOVA, KRUSKALWALLIS ANOVA b) One independent variable and three or more levels with confounding variable (aka covariate): ANCOVA c) One group measured repeatedly with and without covariate: REPEATED MEASURES ANOVA & ANCOVA, FRIEDMAN ANOVA d) Two or more independent variables with 2 or more groups with and without covariate: TWOWAY ANOVA, TWOWAY ANCOVA aka FACTORIAL ANOVA e) Two or more independent variables with 1 group measured repeatedly with and without covariate: TWOWAY REPEATED MEASURES ANOVA & ANCOVA f) Two or more independent variables and mixed methods with and without covariate: MIXED DESIGN ANOVA g) One or more independent variables and the prediction of one or more dependent variables: REGRESSION, MULTIPLE REGRESSION, and Logistic Regression h) Multiple Independent and Dependent Variables: MANOVA & RM MANOVA 3. Create tables to report findings. 4. Compare the utility of multivariate statistical methods in transcultural health research. 5. Interpret reported statistical findings.
1.Identify and test assumptions for statistical tests. 2. Select, conduct and report appropriate statistics to test hypotheses with a) One independent variable and three or more levels (aka groups): ONEWAY ANOVA, KRUSKALWALLIS ANOVA b) One independent variable and three or more levels with confounding variable (aka covariate): ANCOVA c) One group measured repeatedly with and without covariate: REPEATED MEASURES ANOVA & ANCOVA, FRIEDMAN ANOVA d) Two or more independent variables with 2 or more groups with and without covariate: TWOWAY ANOVA, TWOWAY ANCOVA aka FACTORIAL ANOVA e) Two or more independent variables with 1 group measured repeatedly with and without covariate: TWOWAY REPEATED MEASURES ANOVA & ANCOVA f) Two or more independent variables and mixed methods with and without covariate: MIXED DESIGN ANOVA g) One or more independent variables and the prediction of one or more dependent variables: REGRESSION, MULTIPLE REGRESSION, and Logistic Regression h) Multiple Independent and Dependent Variables: MANOVA & RM MANOVA 3. Create tables to report findings. 4. Compare the utility of multivariate statistical methods in transcultural health research. 5. Interpret reported statistical findings.

teaching by explaining main concepts and theorem
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