STAT 183 Midterm Reviewer

A collection of key terms and their definitions related to data analytics, useful for exam preparation.

Data Analytics

The science that analyzes crude data to extract useful knowledge, involving pattern recognition and data-driven decision making.

Three Vs of Big Data

Volume, Variety, Velocity - dimensions that define the characteristics and challenges of big data.

Hyperparameters

Values set by the user in an optimization method, such as the number of clusters in k-means clustering.

CRISP-DM

Cross-Industry Standard Process for Data Mining; a non-rigid framework for data mining methodologies.

Data Mining

The process of discovering patterns in large datasets to derive essential insights.

Descriptive Analytics

The process of summarizing and interpreting historical data to describe what has occurred.

Predictive Analytics

The use of data and statistical algorithms to identify the likelihood of future outcomes based on historical data.

Clustering

An unsupervised learning technique that groups data objects based on information found in the data.

Attribute

A characteristic of an instance in a dataset, often synonymous with variable or feature.

Data Visualization

The graphical representation of information and data, helping to identify trends, outliers, and patterns.

Support Count

The number of transactions that contain a particular itemset in the context of association rules.

Lift (Interest Factor)

The ratio of the confidence of a rule to the support of the itemset in its consequent, indicating correlation strength.

Outlier

An anomaly or unusual value in a dataset that deviates significantly from the majority of the data.

Data Quality Dimensions

Factors such as accuracy, completeness, consistency, timeliness, validity, and uniqueness that determine the quality of data.

Feature Selection

The process of selecting a subset of relevant features for use in model construction.

Sampling

The process of selecting a representative subset from a population for analysis to reduce the cost and time involved.

Algorithm

A self-contained, step-by-step set of instructions for solving a problem or performing a task.

A Priori Principle

The theorem stating that if an itemset is frequent, then all of its subsets must also be frequent, impacting frequent itemset generation.