Answer:
The correct answer is letter "B": A personal interest.
Explanation:
Businesses based on consumers' personal interests attempt to provide a tailored good or service. The competitive advantage of the organization relies on the uniqueness of the product they can provide to their clients compared to competitors who tend to offer products with wide features to cover the larger amount of needs possible.
Conducting businesses driven by customers' personal interests requires constant studies of consumer patterns to adapt in front of market changes and segmentation to identify what sector of the market the company will dedicate their efforts to.
Answer:
d) 6.33
Explanation:
The computation of the expected dividend a year from now is shown below:
As we know that
Price of the stock = Expected dividend ÷ (Required rate of return - growth rate)
Expected dividend = Price of the stock × (Required rate of return - growth rate)
= $63.25 × (0.17 – 0.07)
= $6.325
hence, the correct option is d. $6.33
We simply applied the above formula so that the correct value could come
And, the same is to be considered
In the year 2013, the nation that had the highest GDP per capita out of the options was Switzerland.
In 2013, Switzerland had the very high GDP per capita of $88,109.49 which put it higher than the United States and Brazil.
This high GDP per capita meant that the Swiss economy was strong and that the people were mostly well off.
Find out more on GDP per capita at brainly.com/question/1072073.
Answer:
Switzerland the answer
Answer:
Harper investment 160,000
building over fair value 16,000
royalty over fair value 34,000
cash 200,000
----
2017 entries:
loss on Harper Investment 32,000
Harper investment 32,000
---
Cash 4,000
Harper investment 4,000
----
Unrealized gain 2,000
Harper Investment 2,000
---
royalty over fair value 1,700
bulding over fair value 1,600
harper investment 3,300
---
2018 entries:
Harper Investment 16,000
Gain on Harper Investent 16,000
----
Cash 4800
Harper investment 4800
----
Unrealized gain 1,600
Harper Investment 1,600
---
royalty over fair value 1,700
bulding over fair value 1,600
harper investment 3,300
Explanation:
400,000 x 40% = 160,000
40,000 increase infair value of building x 40% = 16,000
royalty 85,000 x 40% = 34,000
total equity value 200,000
payment of 200,000
no goodwill.
amortization:
building: 16,000 / 10 = 1,600
royalty: 34,000 / 20 = 1,700
2017
loss: 60,000 x 40% = (32,000)
dividends 10,000 x 40% = (4,000)
unrealized gain: it kept 15,000/90,000 = 0.1667 = 16.67%
90,000 - 30,000 = 30,000 gain x 16.67% = 5,000 unrealized gain
5,000 x 40% = 2,000
2018
income 40,000 x 40% = 16,000
dividends 12,000 x 40% = (4,800)
unrealized gain kept 30%
80,000 - 50,000 = 30,000 x 30% = 9,000
the company has 40% so 9,000 x 40% = 3,600 unrealized
as we recognize 2,000 before we adjust for the difference of 1,600
Answer:
Explanation:
Data analysis is a process used to explore, refine, modify, and model the data for finding useful information, making conclusions, and making decisions. Data analysis is a process used to obtain raw data and to make it more user-friendly by decision-making. The data is collected first, and then analyzed to answer questions, test hypotheses, or reject theories.
Descriptive analysis or statistics are one of the three basic parts of statistics science. It is the statistics about compiling, collecting, summarizing and analyzing numerical data. The main difference of descriptive statistics from inferential statistics or inductive statistics with more appropriate terms is that the goal of descriptive statistics is to express and summarize a data set as quantitative number values or count or sort values, and about the character of the statistical population that is accepted to represent such data as inferential statistics. is not the goal of obtaining analytical expressions for predictive or hypothesis testing. Even though the analysis of quantitative data is a study aimed at obtaining its main results using inductive statistical analysis, descriptive statistics tools must be used to support formal analysis. For example, a study involving a formal statistical analysis with topics of human behavior typically covers the overall sample size, sample size of important subgroups, average age, male / female ratios of people treated as data subject, and various demographic, social or clinical characters. supplied with tables.
Predictive analytics is a class of data analysis methods that focuses on predicting the future behavior of objects and subjects in order to make optimal decisions. Predictive analytics uses statistical methods, data mining methods, game theory, analyzes current and historical facts to make predictions about future events. In business, predictive models use patterns found in historical and executed data to identify risks and opportunities. Models capture relationships among many factors to make it possible to assess the risks or potential associated with a particular set of conditions, guiding decisions about possible transactions. It is used in actuarial calculations, financial services, insurance, telecommunications, retail, tourism, healthcare, pharmaceuticals and other fields. One of the well-known applications is credit scoring, scoring models process credit history, loans, consumer data and other information and provide an assessment of a potential borrower in terms of prospective solvency and forecast of timely payments on loans. One of the drawbacks of predictive analytics is the weak accounting for qualitative shifts, changes after bifurcation points, since they are built on quantitative, probabilistic methods.
The prescriptive analysis is the third and final phase of the business analysis. Extended prescriptive analysis beyond predictive analysis specifying both the actions necessary to achieve the predicted results and the related effects of decision. This phase of analysis uses the suggestions of the applications of mathematical and computational sciences to take advantage of the results of descriptive and predictive analyzes. Usually, in a first phase a descriptive analysis is made, widely used in the majority of today's business areas and it answers the question of what happened and why. Then a predictive analysis is done or should be done that answers the question of what will happen: historical data is combined with rules, algorithms and occasionally data external to the company or organization to determine a probable event. Finally, the prescriptive analysis phase which aims to recommend actions for the benefit of predictions and show their implications and why they will occur
Answer:
OAR = $4 per machine hour
Explanation:
Plant wide overhead absorption rate (OAR)
= Estimated overhead/Estimated total machine hours
Estimated machine hours = (5 × 1000) +( 8× 2000) = 21,000 machine hours
OAR = $84,000/21,000 machine hour= $4 per machine hour
OAR = $4 per machine hour
B) marginal revenue = marginal cost
C) marginal benefit = marginal cost
D) all of these are true
A profit maximizing competitive firm in a market with NO externalities will produce the quantity of output where
Option D
Explanation:
All of the options are true.
In a highly competitive market, companies set marginal incomes at marginal cost level (MR= MC) in order to make a profit. MR is the pitch of the profit curve, which represents the (D) and price (P) of the demand curve as well.
It is necessary to have positive, or negative economic benefits in the shorter term. The company profits whenever the price exceeds the total average cost. The company loses on the market if premiums are less than average total costs.