Answer: A) A Bicameral Congress
Explanation: The Connecticut Compromise/Great Compromise defined the terms of representation in the Senate and the house of representatives, collectively the bicameral congress. The terms were, each state should have the same number of representation in the senate, regardless of the size of the state while the house of representatives should reflect the population of each state, such that states with smaller population have less members in the house of representatives.
Answer:
Children who live in poverty perform worse on intelligence tests because they are exposed to more pervasive daily stress, which affects how the brain functions and develops, thus causing a dip in IQ scores
Explanation:
- Children from poor families experience a lot of challenges in their daily life, this is because, their needs cannot be fully met by their incapacitated parents or guardians.
- Therefore, this leads to stress, which consequently leads to a dip in their IQ and therefore poor results from IQ tests.
Answer:
The Mexican Cession
Explanation:
Under the terms of the treaty negotiated by Trist, Mexico ceded to the United States Upper California and New Mexico. This was known as the Mexican Cession and included present-day Arizona and New Mexico and parts of Utah, Nevada, and Colorado (see Article V of the treaty).
Answer:
Unique physical appearance, behaviour and intelligent mind.
Explanation:
Humans are significant in the vast universe because of their unique physical appearance, behaviour and mind. Humans are the most powerful social animals on the planet of earth due to their intelligent minds which able them to formed certain technologies which help them to find out the life on other planets which is farther about millions of kilometers from the earth. There is no life on other planets except planet earth so that's why humans are significant in the vast universe.
Due to the fact that only one index has a non-zero value, this encoding type is known as a one-hot encoding. More frequently, our vector could include word counts for a larger text segment. This illustration is referred to as a "bag of words."
The bag-of-words model is a condensing representation being used information retrieval and natural language processing.
This paradigm ignores syntax and even word order while maintaining multiplicity and represents a text (such as a sentence or document) as the bag of its words.
One hot encoding, that is a crucial step in transforming categorical data variables for use by machine and deep learning algorithms, enhances a model's categorization and forecasting accuracy.
To know more about encoding, visit:
brainly.com/question/29677154
#SPJ4