Experimenter Bias
A bias that occurs when researchers' expectations influence the outcome of a study. Crucial for designing research methods that ensure objectivity and reliability.
26 topics found for:
“experimentation”
Between Subjects Design
An experimental design where different groups of participants are exposed to different conditions, allowing for comparison between groups. Important for understanding and applying different experimental designs in user research.
Matched Pairs Design
An experimental design where subjects are paired based on certain characteristics, and then one is assigned to the treatment and the other to the control group. Important for reducing variability and improving the accuracy of experimental results.
Repeated Measures Design
A research design where the same participants are used in all conditions of an experiment, allowing for the comparison of different conditions within the same group. Essential for reducing variability and improving the reliability of experimental results.
Lean UX
A user experience design methodology focused on rapid iteration, collaboration, and learning through experimentation. Essential for creating user-centered designs efficiently and effectively.
Growth Hacking
A marketing technique focused on rapid experimentation across various channels and strategies to identify the most effective ways to grow a business. Important for quickly scaling businesses and achieving significant growth.
Observer Bias
A type of bias that occurs when the observer's expectations or beliefs influence their interpretation of what they are observing, including experimental outcomes. Essential for ensuring the accuracy and reliability of research and data collection.
Design Excursions
Short, exploratory design activities or exercises that encourage creative thinking and experimentation. Important for fostering creativity and innovation in the design process.
A/A Testing
A method of testing two identical versions of a webpage or app to ensure the accuracy of the testing tool. Important for validating the effectiveness of A/B testing tools and processes.
Dev Environment
A development environment where software is created and modified. Crucial for allowing developers to build and experiment with new features.
Technology Exploration
The process of investigating and experimenting with new technologies to understand their potential applications and benefits. Essential for innovation and staying ahead in a rapidly changing technological landscape.
Rapid Experimentation
The practice of quickly testing and iterating on ideas to validate assumptions and learn from user feedback in a short time frame. Essential for agile development and making data-driven decisions efficiently.
Continuous Discovery
An ongoing process of learning about user needs and validating assumptions through continuous research and experimentation. Crucial for staying responsive to user needs and improving products iteratively.
Product Team
A cross-functional team focused on solving customer problems and achieving business outcomes, with a strong emphasis on discovery, experimentation, and continuous improvement. Crucial for creating valuable and innovative products that meet user needs and drive business success through iterative development and close collaboration with stakeholders.
Innovation Culture
An organizational environment that encourages and supports creative thinking, risk-taking, and the pursuit of new ideas. Essential for fostering continuous improvement and breakthrough advancements.
Behavioral Economics
The study of psychology as it relates to the economic decision-making processes of individuals and institutions. Essential for understanding and influencing user decision-making and behavior in economic contexts.
Worst Possible Idea
A brainstorming technique where participants intentionally suggest bad ideas to spur creative thinking and overcome mental blocks. Important for fostering creativity and out-of-the-box thinking during ideation sessions.
Placing Bets
A strategic approach where multiple potential solutions are tested to identify the most promising one. Crucial for innovation and reducing risk in decision-making.
Outliers
Data points that differ significantly from other observations and may indicate variability in a measurement, experimental errors, or novelty. Crucial for identifying anomalies and ensuring the accuracy and reliability of data in digital product design.
Expectation Bias
A cognitive bias where individuals' expectations influence their perceptions and judgments. Relevant for understanding how expectations skew perceptions and decisions among users.
Behavioral Game Theory
The study of strategic decision making, incorporating psychological insights into traditional game theory models. Useful for understanding complex user interactions and designing systems that account for strategic behavior.
Allais Paradox
A decision-making paradox that shows people's preferences can violate the expected utility theory, highlighting irrational behavior. Important for understanding inconsistencies in user decision-making and designing better user experiences.
A/B Testing
A method of comparing two versions of a webpage or app to see which performs better in terms of user engagement or conversions. Crucial for designers and product managers to test variations and optimize user experience and performance.
Spike
A short, time-boxed period used in Agile development to research a concept or explore a new technology. Important for reducing uncertainty and risk in development.
ModelOps
ModelOps (Model Operations) is a set of practices for deploying, monitoring, and maintaining machine learning models in production environments. Crucial for ensuring the reliability, scalability, and performance of AI systems throughout their lifecycle, bridging the gap between model development and operational implementation.
MMF
Minimum Marketable Feature (MMF) is the smallest set of functionality that delivers significant value to users and can be marketed effectively. Crucial for prioritizing development efforts and releasing valuable product increments quickly, balancing user needs with business objectives.