Multivariate normality testing plays a critical role in modern statistical analysis by evaluating whether a multivariate dataset conforms to the assumptions of a normal distribution. Such assessments ...

Normality testing is a fundamental component in statistical analysis, central to validating many inferential techniques that presume Gaussian behaviour of error terms ...

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 ...

Understanding some statistics is important for general science literacy. Below are some common statistics resources that may be useful for your project work. To support your professional development, ...

Successful completion of this course demonstrate your achievement of the following learning outcomes for the MS-DS program: Define a composite hypothesis and the level of significance for a test with ...

The Statistical & Data Sciences (SDS) Program links faculty and students from across the college interested in learning things from data. At Smith, students learn statistics by doing—class time ...

Statistical significance is a critical concept in data analysis and research. In essence, it’s a measure that allows researchers to assess whether the results of an experiment or study are due to ...

When business researchers analyze data, they often rely on assumptions to help make sense of what they find. But like anyone else, they can run into a whole lot of trouble if those assumptions turn ...