Answer:
grouping the data into bins
Explanation:
Grouping the data into bins-
It refers to the method of grouping the objects according to the classification, into different bins, is referred to as the method of grouping the data into bin.
From the given scenario of the question,
The Turquoise Oasis Spa, classify the orders into various bins, according to the cases 1 to 10 , 11 to 20... and so on, it helps to make the process faster and easy to perform.
Hence, the scenario of the question, is an example of grouping the data into bins.
Answer:
The supply curve will shift to the right.
Explanation:
Whenever there is increase in supply of goods, due to any reasons the supply curve moves to right.
Here, as with the introduction of new technology, the cost of widgets one of the key inputs to the production of whatchamacallits, is reduced,
Accordingly, with the reduction in price of inputs the cost for manufacturers will decrease and they will produce more.
As a result the supply for the product whatchamacallits will increase, and with that the supply curve will move right.
Answer:
Sales-Oriented Pricing objective
Explanation:
Sales-oriented pricing objective focuses on increasing sales and gaining a greater market share.
This strategy prioritizes increasing sales over increasing profits, and it can be achieved by cutting costs and reducing prices to attract more customers.
Answer: BP = BD(WD) + BE(WE)
1 = 0.86(1-WE) + 1.39WE
1 = 0.86-0.86WE + 1.39WE
1 = 0.86 + 0.53WE
-0.53WE = -0.14
0.53WE = 0.14
WE = 0.14/0.53
WE = 0.2641509434
WD = 1 - WE
WD = 1 - 0.2641509434
WD = 0.7358490566
The dollar amount of investment in stock D = 0.7358490566 x $215,000
= $158,207.54
Explanation: The beta of the portfolio is 1, which corresponds to the beta of the market. The beta of the portfolio equals beta of each stock multiplied by the percentage of fund invested in each stock(weight). The weight of stock D is equal to 1 - weight of stock E. Therefore, we need to make weight of stock E the subject of the formula by solving the problem mathematically and collecting the like terms. The weight of stock E is 0.2641509434. The weight of stock E will be subtracted from 1 so as to obtain the weight of stock D, which is 0.7358490566. The dollar amount of stock D equal to $215,000 multiplied by 0.7358490566, which is $158,207.54.
Somebody whose job is to provide analytics or research should always be someone who is very good at quantitative analysis. They should be good with math and numbers, because their job is to analyze a business. The same goes for research. A good researcher is good at math because they have to analyze large datasets. This person would also be pretty detail-oriented because they need to make sure that they are not making small mistakes, as small mistakes could result in poor decisions that come out of their analysis.
Does that make sense?
