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Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.
Seven Key points for PCA: [9] 1. The Personal significance principle: The material needs to focus on meaning and it must be classified as significant to the language learner. [9] An example of this would be having language students fill out a check for an item they would like to buy. [9] 2.
The third analysis of the introductory example implicitly assumes a balance between flora and soil. However, in this example, the mere fact that the flora is represented by 50 variables and the soil by 11 variables implies that the PCA with 61 active variables will be influenced mainly by the flora at least on the first axis).
Positive psychology is the scientific study of conditions and processes that contribute to positive psychological states (e.g., contentment, joy), well-being, positive relationships, and positive institutions. [1] [2]
Resilience: The construct called "resilience" is characterized as positive coping and adaptation in the face of risk or adversity. [18] It is the "positive psychological capacity to rebound, to 'bounce back' from adversity, uncertainty, conflict, failure, or even positive change, progress, and increased responsibility" (Luthans, 2002, p. 702). [19]
The levels of analysis of positive psychology have been summarized to be at the subjective level (i.e., positive subjective experience such as well being and contentment with the past, flow and happiness in the present, and hope and optimism into the future); the micro, individual level (i.e., positive traits such as the capacity for love ...
Sparse principal component analysis (SPCA or sparse PCA) is a technique used in statistical analysis and, in particular, in the analysis of multivariate data sets. It extends the classic method of principal component analysis (PCA) for the reduction of dimensionality of data by introducing sparsity structures to the input variables.
Positive behavior support (PBS) uses tools from applied behaviour analysis and values of normalisation and social role valorisation theory to improve quality of life, usually in schools. PBS uses functional analysis to understand what maintains an individual's challenging behavior and how to support the individual to get these needs met in more ...