Answer:
The data-mining technique that creates a report or visual representation is summarization.
Explanation:
The business world has changed drastically over the years in terms of marketing and service delivery because of growth in technology. The use of machines and internet has caused a greater need for access and analysis of information in such a way that can make a business thrive in the market. This means that most businesses have to look into better data-mining techniques that can assist them in the competitive business environment.
The different data mining techniques include; association-rule learning, classification, summarization and regression. They are explained further as follows:
1. Association-rule learning: this is a machine learning technique that discovers a relationship between large databases using the concept of strong rules.
2. Classification: this technique finds similarities in features of two or more data sets and groups them into the same category.
3. Regression: this is a predictive technique that is used to identify and analyse the likelihood of a specific variable.
4. Summarization: this technique takes the results from the data and puts it in a way that it is short and understandable by most people. It usually involves the use of tables and other data summarization software like Excel sheets to represent the data in a way that conclusions can easily be drawn. Data summarization is important especially in the digital world where large amounts of data are available for analysis and transfer. This technique helps in breaking down huge data into short comprehensible reports that can easily be used for quick decision making.
Answer:
5.75%
Explanation:
The computation of the yield on a bond with three years to maturity is shown below:
Given that
Yield on a one-year bond is 3%
The expected yield on one-year bonds for the next two years is 5% and 4%
And, the liquidity premium is 1.75%
So, the yield on a bond with three years to maturity is
= (3% + 5% + 4%) ÷ 3 years + 1.75%
= 4% + 1.75%
= 5.75%
Answer: $109.3 per machine hour
Explanation: We can compute total production engineering cost per hour by using following equation :-
but first we need to calculate variable cost at 9600 hours :-
= $856,320
now,
=$109.3 per machine hour
