When considering older adolescents (15 years and older) and early adolescents (8- to 11-year-olds), the true statement is that B. Self-esteem usually becomes more stable as adolescents grow older.
<h3>What is adolescence?</h3>
Adolescence is the period of life between childhood and adulthood, lasting from the ages of 10 to 19 years.
Self-esteem is how we see and value ourselves. It is based on our self-perceptions and beliefs, which can be difficult to change. This is also referred to as self-assurance.
Your self-esteem influences whether or not you like and value yourself as a person. Self-esteem levels tend to fall in early adolescence and rise in later adolescence, but those who have lower self-esteem than others at one point are likely to have lower self-esteem than others at the next point as well.
Therefore, based on the information illustrated, the correct option is B.
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Answer:
The answer is the availability heuristic.
Explanation:
The availability heuristic is a mental short-cut that takes place when a person relies on immediately available, often recent information to justifiy their ideas or take decisions. In the example, when George notices his new professor was young, he was surprised because the only available information he had about psychology teachers was completely different.
This heuristic may result in poor decision-making and even <u>stereotyping</u>.
Answer:
Self-serving bias
Explanation:
Self-serving bias: In psychology, the term "self-serving bias" is defined as a person's propensity or proclivity to "attribute" any of the positive situations or events to his or her self or character and therefore "attribute" any of the negative situations or events to some external factors.
In social psychology, self-serving bias is generally referred to as one of the types of cognitive bias.
In the question above, Lori is using "self-serving bias".
So they could fund money to build buildings, get stuff for the army,etc.
<span>Sensitivity analysis enables you to apply different variables in decision making. Sensitivity analysis is a process of varying the inputs to a model and observing the changes in the outcome. This is a great type of analysis to use when uncertainty is prominent.</span>
