Answer and Explanation:
The computation of the reserve requirement is given below;
Required reserves is
= Deposits - loans - excess reserves
= $400 - $362 - $6
= 32 million
And,
Required reserve ratio is
= Required reserves ÷ Deposits
= 32 ÷ 400
= 8%
In this way, it should be determined so that the correct value & percentage could come
Your answer is.......C) Natalie, who has business experience with accounting, management, and marketing
Answer:
There is one train operator with service from Baltimore to Philadelphia
Explanation:
A natural monopoly occurs when there is high fixed or start-up costs of conducting a business in a specific industry meaning a sole producer provides the good efficiently.
Answer:
$15,000
Explanation:
Calculation to determine How much of the casualty loss will be a tax deduction to Zeta, Inc.
Using this formula
Casualty loss tax deduction=Casualty loss-Insurance recovered
Let plug in the formula
Casualty loss tax deduction=$45,000-$30,000
Casualty loss tax deduction=$15,000
Therefore the amount of the casualty loss that will be a tax deduction to Zeta, Inc. is $15,000
Answer:
The options for this question are the following:
a. 1
b. 2
c. 0.5
d. 1.5
The correct answer is a. 1
.
Explanation:
Group analysis or grouping is the task of grouping a set of objects in such a way that the members of the same group (called a cluster) are more similar, in some sense or another. It is the main task of exploratory data mining and is a common technique in the analysis of statistical data. It is also used in multiple fields such as machine learning, pattern recognition, image analysis, information search and retrieval, bioinformatics, data compression and graphic computing.
Group analysis is not in itself a specific algorithm, but the task pending solution. Clustering can be done using several algorithms that differ significantly in your idea of what constitutes a group and how to find them efficiently. Classical group ideas include small distances between members of the group, dense areas of the data space, intervals or particular statistical distributions. Clustering, therefore, can be formulated as a multi-objective optimization problem. The appropriate algorithm and the values of the parameters (including values such as the distance function to use, a density threshold or the number of expected groups) depend on the set of data analyzed and the use that will be given to the results. Grouping as such is not an automatic task, but an iterative process of data mining or interactive multi-objective optimization that involves trial and failure. It will often be necessary to pre-process the data and adjust the model parameters until the result has the desired properties.
