Answer: If the commercial is TRUE that every additional bite of food tastes as good as the first, the marginal utility from consuming more of the advertised product must be CONSTANT. Option D.
Explanation:
Marginal utility is the additional satisfaction an individual gets, from consuming an additional unit of a product or service.
Therefore, in the scenario given above, if every additional bite of food tastes as good as the first, then the additional satisfaction is just as good as the preceding satisfaction. We can therefore say that the marginal utility gotten from consuming that product is constant.
Answer:
Experience an inward shift of its production possiblity curve.
Explanation:
Production possiblity curve is a graphical representation of the maximum number of products that a company can produce, if it produce only two product using all the resources efficiently. The maximum production possiblity of one product is shown on one side graph and another product on other side to compare which product can be produced to reduce cost and wastage while maximizing the profit. This also help the management to know the effecient use of resources or factor of production; Land, labour, capital and entrepreneurship. Therefore, lack of resources to Cuba have lead it´s economy to decline.
Answer:
The U.S. Congress authorized CTSOs.
Explanation:
Answer:
C. 534 units
Explanation:
The formula to compute the break-even point is shown below:
= (Fixed cost) ÷ (Contribution margin per unit)
where,
Contribution margin per unit = Selling price per unit - Variable expense per unit
= $3 - $0.75
= $2.25
So, the break-even point would be
= $1,201 ÷ $2.25 per unit
= 534 units
Simply we divide the fixed cost by the contribution margin per unit so that the accurate units can come.
Answer:
Because the test statistic is less than the critical value, we can reject the null hypothesis and conclude that the population correlation coefficient is less than zero.
Explanation:
Because the question is based on the hypothesis test of the significance of the correlation coefficient to decide whether the linear relationship in the sample data is strong enough to use to model the relationship in the population. If the tests concludes that the correlation coefficient is not significantly different from zero, it means that the correlation coefficient is not significant.
