Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have ...

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 ...

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...

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 ...

Exploratory Factor Analysis (EFA) is a pivotal statistical approach that enables researchers to uncover latent structures in complex datasets, a process that is increasingly integral to higher ...

Let’s start with a definition of Applied Statistics: Applied Statistics is the root of data analysis. The practice of applied statistics involves analyzing data to help define and determine an ...

In the early 1920s, a trio of scientists sat down for a break at Rothamsted agricultural research station in Hertfordshire, UK. One of them, a statistician by the name of Ronald Fisher, poured a cup ...

Looking to get into statistical programming but lack industry experience? We spoke with several statistical programmers from diverse backgrounds, and one thing became clear—there’s no single path to ...

Their goal is admittedly ambitious: To compete with the Summer Program in Quantitative Methods of Social Research offered by the University of Michigan—considered to be the gold standard in advanced ...

When you use the statistical analysis features in Excel, you are leveraging one of the most powerful tools available for data manipulation and interpretation. Excel is not just a spreadsheet ...