Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

Examples of such models include the normal distribution model and the linear regression model. Nonparametric statistics sometimes use data that is ordinal, meaning it relies not on numbers but on ...

Introduces methods, theory, and applications of linear statistical models, covering topics such as estimation, residual diagnostics, goodness of fit, transformations, and various strategies for ...

For example, modeling the state damaged/not damaged of cells after treated with a certain chemical; and modeling the number of insects caught by a certain kind of trap. These types of situations can ...

A statistical model is autoregressive if it predicts future values based on past values (i.e., predicting future stock prices based on past performance).

Linear regression remains a cornerstone of statistical analysis, ... for example, the Generalised Cross Validation (GCV) ... Estimation Techniques in Linear Regression Models Publication Trend.

The Department of Statistics, Manipal University, will host an International Conference on Linear Algebra and its Applications (ICLAA-2014) in the University from December 18 to 20. The Conference ...