Porque los humanos tienen recursos limitados pero deseos y necesidades ilimitados. Actividades realizadas por otros para nosotros. Recursos que están ampliamente disponibles y que nunca se pueden usar.
(Because humans have limited resources but unlimited wants and needs. Activities done by others for us. ... Resources that are widely available and can never be used up.)
The nature's way is relying on a location principle called retail compatibility. It is where they place their location in a more suitable environment that will fit the category of their business. It could be seen above as because their business is about promoting healthy foods, they are placed near the gym where people in the gym would be attracted to their business.
Answer:
a. $1,375
b. $1,240
Explanation:
FIFO method
FIFO assumes that the inventory to arrive first will be sold first. Inventory values depend on earlier purchases
Inventory = 185 x $5 + 75 x $6
= $1,375
LIFO method
LIFO assumes that the inventory to arrive last will be sold first. Inventory values depend on recent purchases
Inventory = 130 x $7 + 55 x $6
= $1,240
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.
