The statement that the percent sales method for estimating bad debts for a company, will only use those balances in the income statement is False.
<h3>What is the percent of sales method?</h3>
The percent of sales method is one of the methods that companies can use to estimate the bad debts that it expects in a given period. Bad debts refer to those Account Receivables that will not pay the company back even after they have taken goods or services on credit. In order to be able to use the percent of sales method, the sales of a company need to be known.
The sales that a company makes includes both the sales that the company made and the accounts receivable. The Accounts Receivables go to the Balance Sheet and Sales go to the Income Statement. This means that the Balance Sheet balances are used as well as Income Statement balances and not just the latter.
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Answer:
C, Management Information System
Explanation:
Answer: innovator
Explanation:
From the question, we are informed that whenever Andrew considers upgrading his personal computer system, he normally consults with Jeremy, a knowledgeable friend who always has the newest technology.
Regarding the question, Jeremy is an innovator. An innovator is someone who has embraced new ideas and is always trying out new gadgets and technology.
Answer: Option (D) is correct.
Explanation:
The economic efficiency is achieved at a point where demand curve and supply curve intersects each other. This point is known as market equilibrium. The area under the demand curve and above the equilibrium price level is known as consumer surplus.
The area above the supply curve and under the equilibrium price level is known as producer surplus.
Hence, the combine area of consumer surplus and producer surplus have to maximized to have a economic efficiency in an economy.
Answer and explanation:
Regression coefficients portrait the changes in variables after one unit has changed keeping the rest of the predictors of the model the same. While the <em>simple linear regression</em> is predicted from one variable, the <em>multiple regression</em> is predicted for more than one of them.
