Everything about Exploratory data analysis
Approach of analyzing data sets in statistics
In statistics, exploratory data analysis (EDA) or exploratory analytics is an approach of analyzing data sets to summarize their main characteristics, often using statistical graphics and other data visualization methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell beyond the formal modeling and thereby contrasts with traditional hypothesis testing, in which a model is supposed to be selected before the data is seen and tested. Exploratory data analysis has been promoted by John Tukey since 1970 to encourage statisticians to explore the data, and possibly formulate hypotheses that could lead to new data collection and experiments. EDA is different from initial data analysis (IDA), which focuses more narrowly on checking assumptions required for model fitting and hypothesis testing, and handling missing values and making transformations of variables as needed. EDA encompasses IDA. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Exploratory data analysisA 5-minute orientation
- Skim a recent paper: The artificial intelligence advantage: Supercharging exploratory data analysisInfluential work since 2022
- Pick up a classic book: Lines of ThoughtThe most-reprinted book on the subject
- Read the landmark paper: Exploratory data analysisCited 109 times
- Go sideways: John TukeyA closely related topic
- Go sideways: Median polishA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Exploratory data analysis
Exploratory Sequential Data Analysis: Foundations
Exploratory Data Analysis using Python
Exploratory data analysis
Exploratory Spatial Data Analysis
Exploratory Data Analysis
Projection pursuit exploratory data analysis
Exploratory sequential data analysis
🆕 Influential since 2022
The artificial intelligence advantage: Supercharging exploratory data analysis
Exploratory analysis of hyperspectral imaging data
Exploratory functional data analysis
Reinforced Approximate Exploratory Data Analysis
Analysis of cuttings concentration experimental data using exploratory data analysis
📚 Books worth reading
Lines of ThoughtAyelet Even-Ezra · 2021
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- John Tukey John Wilder Tukey (/ˈtuːki/; June 16, 1915 – July 26, 2000) was an American mathematician and statistician, best known for the development of the fast…
- Median polish The median polish is a simple and robust exploratory data analysis procedure proposed by the statistician John Tukey. The purpose of median polish is to…
- Box plot In descriptive statistics, a box plot or boxplot is a method for demonstrating graphically the locality, spread and skewness groups of numerical data through…
- Trimean In statistics the trimean (TM), or Tukey's trimean, is a measure of a probability distribution's central tendency defined as a weighted average of the…
- Five-number summary The five-number summary is a set of descriptive statistics that provides information about a dataset. It consists of the five most important sample percentiles:…
- Statistical graphics Statistical graphics, also known as statistical graphical techniques, are graphics used in the field of statistics for data visualization. Whereas statistics…
- Data analysis Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions…
- L-estimator In statistics, an L-estimator (or L-statistic) is an estimator which is a linear combination of order statistics of the measurements. This can be as little…