Deductive Research
A research approach that starts with a theory or hypothesis and uses data to test it, often moving from general to specific. Essential for validating theories and making informed decisions based on data.
A research approach that starts with a theory or hypothesis and uses data to test it, often moving from general to specific. Essential for validating theories and making informed decisions based on data.
A statistical method used to assess the generalizability of a model to unseen data, involving partitioning a dataset into subsets for training and validation. Essential for evaluating model performance and preventing overfitting in digital product analytics.
Proof of Concept (PoC) is a demonstration, usually in the form of a prototype or pilot project, to verify that a concept or theory has practical potential. Crucial for validating ideas, demonstrating feasibility, and securing support for further development in product design and innovation processes.
A statistical theory that states that the distribution of sample means approximates a normal distribution as the sample size becomes larger, regardless of the population's distribution. Important for making inferences about population parameters and ensuring the validity of statistical tests in digital product design.
A theory of motivation that emphasizes the importance of autonomy, competence, and relatedness in fostering intrinsic motivation and psychological well-being. Important for understanding how to design experiences that support user motivation and well-being.
The tendency for negative information to have a greater impact on one's psychological state and processes than neutral or positive information. Important for understanding and mitigating the impact of negative information.