Analysis of classic assumption test and multiple linear regression coefficient test for employee structural office recommendation

Abstract

The performance appraisal process in Religious High Court Bandar Lampung has not been carried out objectively, but rather a subjectivity element (relationship closeness). Some employees occupy structural positions but do not fulfil competence and promotion principles, so that it has an impact on providing promotion to a position in the judiciary. Multiple Linear Regression method can provide a predictive model for employee recommendations entitled to occupy positions in the agency. The method implementation using SPSS produces an equation Y = 74.177 + 0.035X1 + 0.020X2 - 0.026X3 + 0.045X4 + 0.001X5. This equation is applied to the employee performance values, and it is obtained from 40 employees 26 employees deserve to be given recommendations promotion. Regression performance testing results using 10-cross validation get the correlation coefficient value is 80.66% with MAE value of 2.24% and RMSE 3.88%, which mean has good performance.

Evaluating partial and simultaneous effects of logical-mathematical, visual-spatial, and intrapersonal intelligence on prospective primary teachers’ problem solving

“…4) show that the data has passed the prerequisite tests. The dependent and independent variables are normally distributed, so it has an impact on the test results that also have normally distributed data, or the regression model is close to normal (Alita et al, 2021). In addition, the data also passed the linearity test, where the results had a direct calculation impact and easy interpretation (Baek et al, 2015).…”

“…Data analysis was carried out quantitatively through descriptive statistics and inferential statistics with the help of the SPSS 22 program. The classical assumption test used as a prerequisite test was through 4 stages; normality, linearity, multicollinearity, and heteroscedasticity tests (Alita et al, 2021;Daoud, 2017;Klein et al, 2016). The hypothesis testing used a multiple linear regression test.…”

The Influence of E-Payment and E-Commerce Services on Supply Chain Performance: Implications of Open Innovation and Solutions for the Digitalization of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia

“…Research using the Exact method can obtain accurate results [106]. The data are distributed normally in the normal regression standardized residual PP plot when the data are spread between the diagonal lines and follow the direction of the line [107]. The results of the normality test are shown in Table 6, Normality Test Results.…”

“…Multicollinearity tests are performed to look at the linear relationships between independent variables, because a high correlation between independent variances can make it difficult to distinguish each influence of variable on the dependent variable [107]. A multicollinearity test in this study was carried out to determine the correlations between the independent variables (e-payment services and e-commerce services) or dependent variables (MSME supply chain performance).…”

Comparisons Between Robust Regression Approaches in the Presence of Outliers and High Leverage Points

“…Three underlying assumptions must be fulfilled by the errors term in linear regression analysis. These assumptions are normality, constant variance, and independence assumptions, [1]. In general, the errors are assumed to be independently and identically distributed random variables from normal distribution with mean zero and constant variances.…”