Abstract

The multiple linear regression model of the important regression models used in the analysis for different fields of science Such as business, economics, medicine and social sciences high in data has undesirable effects on analysis results . The multicollinearity is a major problem in multiple linear regression. In its simplest state, it leads to the departure of the model parameter that is capable of its scientific properties, Also there is an important problem in regression analysis is the presence of high leverage points in the data have undesirable effects on the results of the analysis , In this research , we present some of

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In this search, we examined the factorial experiments and the study of the significance of the main effects, the interaction of the factors and their simple effects by the F test (ANOVA) for analyze the data of the factorial experience. It is also known that the analysis of variance requires several assumptions to achieve them, Therefore, in case of violation of one of these conditions we conduct a transform to the data in order to match or achieve the conditions of analysis of variance, but it was noted that these transfers do not produce accurate results, so we resort to tests or non-parametric methods that work as a solution or alternative to the parametric tests , these method

Iron slag is a byproduct generated in huge quantities from recycled remnants of iron and steel factories; therefore, the possibility of using this waste in the removal of benzaldehyde from contaminated water offers an excellent topic in sustainability field. Results reveal that the removal efficiency was equal to 85% for the interaction of slag and water contaminated with benzaldehyde at the best operational conditions of 0.3 g/100 mL, 6, 180 min, and 250 rpm for the sorbent dosage, initial pH, agitation time, and speed, respectively with 300 mg/L initial concentration. The maximum uptake capacity of iron slag was 118.25 mg/g which was calculated by the Langmuir model. Physical sorption may be the major mechanism for the removal of

     The first step in this research is to find some of the necessary estimations in approximation by using certain algebraic polynomials, as well as we use certain specific points in approximation. There are many estimations that help to find the best approximation using algebraic polynomials and geometric polynomials. Throughout this research, we deal with some of these estimations to estimate the best approximation error using algebraic polynomials where the basic estimations in approximation are discussed and proven using algebraic polynomials that are discussed and proven using algebraic polynomials that are specified by the following points and  if   as well as if   .

  For the second step of the work, the estimatio

     In this work, the annual behavior and cross-correlation between three different solar-ionospheric indices were evaluated: Smoothed Sunspot Number (SSN), Ionospheric T-Index (T-index), and Solar Flux (F10.7 cm) index during solar cycles 23 and 24. The annual behavior for the three tested indices of the maximum and minimum years of the two solar cycles was studied. The correlative conducts between the studied indices were evaluated for the studied periods (1996-2008) and (2008-2019) of the 23rd and 24th solar cycles. The annual correlation between the studied indices was represented by the linear regression equation. The suggested mutual correlation equation gave a good agreement with the observed annual average values of the test

In this paper, a theoretical study of the energy spectra and the heat capacity of one electron quantum dot with Gaussian Confinement in an external magnetic field are presented. Using the exact diagonalization technique, the Hamiltonian of the Gaussian Quantum Dot (GQD) including the electron spin is solved. All the elements in the energy matrix are found in closed form. The eigenenergies of the electron were displayed as a function of magnetic field, Gaussian confinement potential depth and quantum dot size. Explanations to the behavior of the quantum dot heat capacity curve, as a function of external applied magnetic field and temperature, are presented.