EDA

Exploratory Data Analysis (EDA)

A systematic approach to summarizing and understanding the main characteristics of a dataset using graphical and non-graphical methods.

Descriptive Statistics

Statistics that report facts and summarize raw data, including measures like mean, median, mode, and distribution.

Inferential Statistics

Statistics that involve drawing conclusions and making predictions about a population based on a sample.

Uncertainty in Statistics

The degree of doubt or variability in data that affects the reliability of statistical conclusions.

Structured Data

Data that is organized in a defined format, often in rows and columns, allowing for easy access and analysis.

Unstructured Data

Data that doesn’t have a predefined format or structure, making it complex to process and analyze.

Continuous Data

Numerical data that can take on any value in a given range, such as temperature or time.

Discrete Data

Numerical data that can only take specific integer values, like the number of students.

Categorical Data

Data that represents characteristics and can only take on certain values, such as type of vehicle or gender.

Time Series Data

Records successive measurements of a variable over time, used for analysis of trends.

Mean

The average value of a dataset, calculated by summing all values and dividing by the count of values.

Median

The middle value in a dataset when it is ordered from least to greatest.

Mode

The most frequently occurring value in a dataset.

Outlier

An observation that lies far from the other values in a dataset, potentially indicating variability or error.

Central Tendency

A statistical measure that identifies a single score as representative of an entire distribution.

Statistics

The field of study concerned with collecting, analyzing, interpreting, presenting, and organizing data.

Field of Statistics

The practice and techniques used to analyze data to derive insights and inform decisions.

Inferential Drawings

Conclusions made based on observations in descriptive statistics to make predictions about a larger population.

Bias in Data Interpretation

A tendency to favor a particular perspective, which can lead to misinterpretation of data.

Graphical Methods in EDA

Visual techniques used to represent data characteristics and patterns, such as histograms and scatter plots.

Non-Graphical Methods in EDA

Statistical methods that summarize data numerically, like summary statistics and correlation coefficients.