1. durability- objects used as money must withstand physical and tear
2. portability- people need to be able to take money with them as they go about their business
3.divisibility-to be useful, money must be easily divided into into smaller denominations, or units of value
4.uniformity- any two units of money must be uniform or the same in the terms of what they will buy.
5.limited supply- money must be available only in limited quantities
6.acceptability- Everyone must be able to exchange the money for goods and services
Self-interest of course! Though you gave us no clue as to who is Adam... You can tell it's mostly self-interest due to the fact that he hasn't taken any class or anything on it. Looks to me that he genuinely just loves cooking!
Answer:
Anyone who is injured by a defective product may sue the manufacturer, merchants and all others who handled the product.
Explanation:
Strict liability is a legal doctrine that holds a person responsible for the damages or loss caused by his or her acts or omissions. In torts, strict liability is the doctrine that imposes liability on a party or person without a finding of fault. A finding of fault would be negligence or tortious intent.
Strict liability is an important factor in maintaining safety in high-risk environments by encouraging individuals, employers, and other parties to implement the means to prevent injuries and damages. Construction, manufacturing, and other potentially dangerous work settings are typically subject to strict liability.
The answer is...
Liabilities
Answer:
3. the sampling distribution of the sample mean is normally distributed.
5. the value of the sample mean varies from sample to sample.
Explanation:
We develop confidence interval for population mean because
a. the sampling distribution of the sampling mean is normally distributed. For us to do this we must first ensure that the sample mean is large enough
B. The value of the sample mean is not the same for all samples it varies from sample to sample. Therefore it it is better that an internal is given with the probability that the parameter falls into it.
