Speeding up the exploratory data analysis process using flexible automation and consistent reporting allows analysts to deliver analyses quickly while ensuring precise, accurate results.

The Exploratory Data Analysis Problem. The prudent scientist must interrogate the data with a laundry list of statistical questions to determine the data’s fit-for-use in AI and ML projects. Are there ...

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 ...

Gaea Leinhardt, Samuel Leinhardt, Exploratory Data Analysis: New Tools for the Analysis of Empirical Data, Review of Research in Education, Vol. 8 (1980), pp. 85-157 ...

The purpose of the Journal of Computational and Graphical Statistics is to improve and extend the use of computational and graphical methods in statistics and data analysis. Established in 1992, this ...

Microsoft Excel: The Swiss Army knife of data analysis, current versions of the Microsoft Excel spreadsheet can store up to 1 million rows of data. It also has basic tools for manipulating and ...

Introduces exploratory data analysis, probability theory, statistical inference, and data modeling. Topics include discrete and continuous probability distributions, expectation, laws of large numbers ...

Analysis of the data includes simple query and reporting, statistical analysis, more complex multidimensional analysis, and data mining. The information frequently is stored in a data warehouse, a ...

An exploratory data analysis has been performed on the dataset to explore the effects of different factors like holidays, fuel price, and temperature on Walmart’s weekly sales. Additionally, a ...