Answer:
C $30,000
Explanation:
. A $30,000 result has a 35 percent chance of occurring, but the entity cumulatively has a 55 percent chance of receiving at least a $30,000 tax benefit. As a result, $30,000 is the appropriate amount to recognize.
Answer:
B. Implied warranty of fitness
Explanation:
An implied warranty of fitness for an specific purpose refers to the fact that if the seller of a product knows that the product will be used for an specific purpose and that the buyer is purchasing that product for that using it that way, then an implied warranty of fitness is formed. In this case, the seller knew that Palmer was going to carry 5,000 pounds in the truck and therefore, by offering a certain truck to Palmer, an implied warranty of fitness was formed stating that the truck could carry that load.
Answer:
a.Take a lower level job in a human resources department for experience.
Explanation:
For Brenda to be able to progress to the next stage, she needs to address the issue holding her back. From the feedback that Brenda has received, she needs work experience to run a human resource departments. Brenda should then find a way of adding work experience to her credentials.
The most appropriate way for her to gain experience is by taking a lower level job in a human resource department. By doing so, Brenda will gain hands on experience on human resources operations. She will get an opportunity to work under a manager. That way, she will acquire the practical skills of a human resources manager.
The answer is A sounds we make without forming words
Answer:
In order to make a decision utilizing a decision tree, you must:___________
b. begin at Time 0 and work towards the most distant point in time.
Explanation:
Decision trees are built up by starting from the present with the overarching objective (goal) in mind. Then, one classifies the information along various branches and leaf nodes, with each branch representing the outcome of an alternative route or a question answered based on the likelihood of the event happening. Each leaf node represents a class label (decision taken after computing all attributes). This structure can be used to predict likely values of data attributes.