Answer:
Prescriptive analytics
Explanation:
Prescriptive Analytics refers to the data analytics field that specializes on determining the best approach in a situation, based on the data accessible. It is linked towards both descriptive analytics as well as predictive analytics yet highlights valuable insights rather than data analysis.
Prescriptive analytics collects information with its systems from either a range of descriptive or predictive databases and relates it to the choice-making process. It involves mixing existing conditions with alternative actions to evaluate how well the outcome would be influenced by each.
It can also assess the effects of judgment, based on various potential future situations. The discipline draws inspiration from applied mathematics, using a number of statistical techniques to construct and re-create potential judgment trends that could have different effects on an entity.
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Answer:
a: 12.8%
Explanation:
Standard Deviation would be calculated with the probability approach since there is probability given in the question.
- Formula of Standard Deviation and the solution is given in the pictures below.
- Although ERR the required part to calculate Standard Deviation is calculated in the text.
Calculating ERR:
ERR= Sum of Probabilities × Rate of returns.
In our question = ERR= 0.2 × 30% + 0.5 × 10% + 0.3 × (-6%) = 0.128 = 12.8%
Thus, by putting all the values in the formula you will get the answer 12.8%.
Answer and Explanation:
The computation of the total budgeted selling and administrative expenses is shown below;
Utilities expense $2,800
Administrative salaries $100,000
Sales commissions 5 % of sales i.e. 5% of $860,000 $43,000
Advertising $20,000
Depreciation on store equipment $50,000
Rent on administration building $60,000
Miscellaneous administrative expenses $10,000
total budgeted selling and administrative expenses $285,800
Answer:
E) 1920
Explanation:
The computation of the maximum items in process is shown below:
= Number of maximum target cycle time × normal processing rate per minute × number of minutes in one hour
= 16 hours × 2 × 60 minutes
= 1,920
Simple we multiply the all items which are given in the question, so that the accurate value can come i.e maximum target cycle time, normal processing rate per minute and the number of minutes in one hour
