Answer:
A. Chocolate Candy Bars Total Utility (utils) Marginal Utility (utils
0 0 —
1 25 25
2 42 17
3 54 12
4 62 8
5 66 4
6 65 –1
2. Soda
Explanation:
A.Chocolate Candy Bars Total Utility (utils) Marginal Utility (utils)
0 0 —
1 25 25
2 42 17
3 54 12
4 62 8
5 66 4
6 65 –1
1. In a situation where the consumption go up from 0 to 1, this means that total utility will from 0 to 25.
Therefore the , marginal utility will be 25 (25 – 0).
2. Total utility will be 42(25+17)
3. Marginal utility will be 12 (54-42)
4. The total utility for quantity of 5 is 66, while the marginal utility is 4.
Hence the total utility will be 62 (66 – 4) while marginal utility will be 4(12-8)
6. Total utility will be 65(66-1)
B. Based on( A )above Marco already has two candy bars, which gave him a total utility of 42 this means that when we Add soda his utility would increase to 64 (42 + 22)
And in a situation where he consumes four candy bars which is 2 candy bars + another 2 extra candy bars this means his utility will be only 62.
Based on this Soda will be the preferred one
Answer:
MPLF/MPLC; becomes steeper
Explanation:
The slope of a country's production possibility frontier with cloth measured on the horizontal and food measured on the vertical axis in the specific factors model is equal to MPLF/MPLC and it becomes steeper as more cloth is produced.
Where
- MPLC is Marginal Product of Labor for Cloth.
- MPLF is Marginal Product of Labor for Food.
Cognitive evaluation theory would question the use of money as a motivator because external motivational tools may lower intrinsic motivation because people will start working to get the reward, NOT because they are intrinsically motivated or challenged.
Franchising is the practice of paying a company to use its name, resources and operation systems.
Somebody whose job is to provide analytics or research should always be someone who is very good at quantitative analysis. They should be good with math and numbers, because their job is to analyze a business. The same goes for research. A good researcher is good at math because they have to analyze large datasets. This person would also be pretty detail-oriented because they need to make sure that they are not making small mistakes, as small mistakes could result in poor decisions that come out of their analysis.
Does that make sense?
