Multiple Regression
A statistical technique that uses several explanatory variables to predict the outcome of a response variable, extending simple linear regression to include multiple input variables.
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“product features”
Data Distribution
The spread and pattern of data values in a dataset, often visualized through graphs or statistical measures.
Implementation Intentions
A self-regulation strategy in the form of "if-then" plans that can lead to better goal attainment and behavior change.
Rapid Experimentation
The practice of quickly testing and iterating on ideas to validate assumptions and learn from user feedback in a short time frame.
Illusory Superiority
A cognitive bias where individuals overestimate their own abilities, qualities, or performance relative to others.
Risk Compensation
The theory that people adjust their behavior in response to the perceived level of risk, often taking more risks when they feel more protected.
Empathy in Design
The practice of deeply understanding and sharing the feelings of users to create products and services that truly meet their needs.
Behavioral User Experience
The application of behavioral science principles to improve the design and usability of digital products, focusing on user behavior and interactions.
Train/Test
A method of splitting a dataset into two subsets: one for training a model and another for testing its performance.