The fourth one should be the correct answer
Answer:
Roosevelt appeals to the logic of the audience by noting that the interests of the people are not considered in a one-party government.
Step-by-step explanation:
Answer:
The distance is D. 21.25 ft.
Step-by-step explanation:
This is an example of a distance problem: <em>Find the distance traveled by an object during certain time period if the velocity of the object is known at all times.</em>
We are given a table of values for time and speed

If the speed remains constant, then the distance problem is easy to solve by means of the formula
distance = speed x time
Therefore, the total distance is

The two best examples of long-term needs that people need to save for includes:
- college education
- medical emergencies
<h3>What is a Long-term needs?</h3>
This refer to those needs that one will be will be needing in the future or for a very long time.
The need to saving up for college is important if one want to have a bright future or a better salary.
The need to saving up for medical emergencies is also crucial because we're all human beings who, at some point, will deteriorate physically.
Therefore, the Option A and C is correct,
Read more about Long-term needs
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Answer:
Monte Carlo simulation
Step-by-step explanation:
In queue modeling questions, customers arrive with a random order in a certain time span and the service times are considered to be constant. This constitutes a randomness problem due to the interarrival times of the customers. Monte Carlo simulations are used for solving the parameters than entail variations or uncertainties. In order to solve this situation, Monte Carlo method uses a distribution pattern instead of a single variable by using the constraints given by the user and gives all the possible solutions with their possibilities. Thus, when all the possible inputs are introduced into a Monte Carlo algorithm, all the possible outcomes and probabilities are given as outcomes. Since, all the interarrival times can be introduced into a Monte Carlo algorithm, all the queue possibilities can be known. Thus, this problem type can be solved with Monte Carlo simulation due to the randomness.