This time we are looking on the crossword clue for: Hardly happy.
it’s A 12 letters crossword puzzle definition. See the possibilities below.
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Possible Answers: SAD, IRATE, BLUE, DISTRESSED.
Last seen on: –Premier Sunday – King Feature Syndicate Crossword – Mar 13 2022s
–The Washington Post Crossword – Sep 26 2020
Random information on the term “SAD”:
Sadness is an emotional pain associated with, or characterized by, feelings of disadvantage, loss, despair, grief, helplessness, disappointment and sorrow. An individual experiencing sadness may become quiet or lethargic, and withdraw themselves from others. An example of severe sadness is depression. Crying is often an indication of sadness.
Sadness is one of the “six basic emotions” described by Paul Ekman, along with happiness, anger, surprise, fear, and disgust.
Sadness is a common experience in childhood. Some families may have a (conscious or unconscious) rule that sadness is “not allowed”, but Robin Skynner has suggested that this may cause problems, arguing that with sadness “screened off”, people can become shallow and manic. Pediatrician T. Berry Brazelton suggests that acknowledging sadness can make it easier for families to address more serious emotional problems.
Sadness is part of the normal process of the child separating from an early symbiosis with the mother and becoming more independent. Every time a child separates a little more, he or she will have to cope with a small loss. If the mother cannot allow the minor distress involved, the child may never learn how to deal with sadness by themselves. Brazelton argues that too much cheering a child up devalues the emotion of sadness for them; and Selma Fraiberg suggests that it is important to respect a child’s right to experience a loss fully and deeply.
Random information on the term “BLUE”:
In statistics, linear regression is an approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables (or independent variables) denoted X. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, the process is called multiple linear regression. (This term is distinct from multivariate linear regression, where multiple correlated dependent variables are predicted, rather than a single scalar variable.)
In linear regression, the relationships are modeled using linear predictor functions whose unknown model parameters are estimated from the data. Such models are called linear models. Most commonly, the conditional mean of y given the value of X is assumed to be an affine function of X; less commonly, the median or some other quantile of the conditional distribution of y given X is expressed as a linear function of X. Like all forms of regression analysis, linear regression focuses on the conditional probability distribution of y given X, rather than on the joint probability distribution of y and X, which is the domain of multivariate analysis.