Terms and definitions from all courses

Glossary
Advanced Data Analytics

Terms and definitions from all courses

A

A/B testing: A way to compare two versions of something to find out which version performs better


Absolute values: (Refer to observed values)
Accuracy: Refers to the proportion of data points that were correctly categorized
Action: A Tableau tool to help an audience interact with a visualization or dashboard by allowing control of selection


Active listening: Refers to allowing team members, bosses, and other collaborative stakeholders to share their own points of view before offering responses


AdaBoost: (Refer to adaptive boosting)


Adaptive boosting: A boosting methodology where each consecutive base learner assigns greater weight to the observations incorrectly predicted by the preceding learner Addition rule (for mutually exclusive events): The concept that if the events A and B are mutually exclusive, then the probability of A or B happening is the sum of the probabilities of A and B


Adjusted R²: A variation of R² that accounts for having multiple independent variables present in a linear regression model


Affinity: The metric used to calculate the distance between points/clusters


agg(): A pandas groupby method that allows the user to apply multiple calculations to groups of data


Agglomerative clustering: A clustering methodology that works by first assigning every point to its own cluster, then progressively combining clusters based on intercluster distance


Aggregate information: Data from a significant number of users that has eliminated personal information


Algorithm: A set of instructions for solving a problem or accomplishing a task