The answer looks it might be B. Why?
- Choice A: The Electoral College does not encourage the citizens of the US to vote in state level elections.
- Choice C: The Electoral College does not increase national political attention on individual states, although the Electoral College in the 2016 election did ignite a national debate on whether or not the US should keep the Electoral College system.
- Choice D: The Electoral College does not provide federal revenue to state-run educational programs.
- Choice E: The Electoral College does not act as a liasion for communication between state and national legislators since it is not a "physical" system.
• Additional Information:
--- The purpose of the Electoral College is to be a compromise between the election of the president by the vote of Congress and the popular vote of the people.
--- The founding fathers established the Electoral College in the United States Constitution, believing that it would be both a buffer and provide fair power to all states regardless of size.
<u>Answer:
</u>
The major political parties in the united states get citizens more interested by including in their manifestos and promising to resolve the issues that are of major concern of majority citizens.
<u>Explanation:
</u>
- The political parties intelligently devise the issues that the current politics can be made to revolve around and be taken political advantage from.
- The issues that bother the citizens on large scale are considered by political leaders as the main issues to fight the elections on so that they are favored by the voters in the elections.
Dictatorship. It does not give anyone power to make a decision other than its own self appointed government. Democracy is the opposite.
Answer:
how about i take your points
Explanation:
Learning takes place in a connectionist network through a process of <u>back propagation</u> in which an error signal is transmitted starting from the property units.
<u>Explanation</u>:
Back propagation is a set of rules used for learning about the artificial neural networks using gradient descent. The gradient of the error function is calculated with respect to the neural network's weights.
This algorithm can be efficiently used to calculate the derivatives. Connectionist networks helps in arranging the neurons into a network. This network defines the arrangement of neurons, transmission function of neuron and a learning rule.
In back propagation, the error signal is transmitted from the property units.
