Answer:
loss of $5,000 on adjustment of trading debt investments
Explanation:
The comprehensive income statement records gains and losses on the trading debt investments.
By the end of 2022 the trading debt investments had fallen in value to $11,000 from $15,000 representing a loss of $5,000 to be adjusted in the income statement.
Answer: the strategy is called pull.
Explanation:
The primary difference between push and pull marketing lies in how consumers are approached. In push marketing, the idea is to promote products by pushing them onto people. On the other hand, in pull marketing, the idea is to establish loyalty drawing consumers to the products with advertising and sales promotion activities.
Answer:
Total expending 21,320
Explanation:
Assuming the administrative expense are also paid on cash during the period
1,300 units x $4.20 = 5,460 Variable expending
19,240 fixed cost - 3,380 depreciation (non-monetary) = 15,860 Fixed expending
Total expending 5,460 + 15,860 = 21,320
<u>Remember:</u>
Depreciation and amortization are non-monetary term, they don't involve a cash disbursement.
Answer:
A) Advanced Customer Segmentation
Explanation:
Advanced Customer Segmentation involves using psychographic data about segments to gain in their interests. With advanced customer segmentation, segments are filled with customers with like interests. These segments are special because due to the fact that you as a marketer knows their taste and wants, they trust you to the extent of willing to become your fulltime customers. These segments are likely to spend money with you once this level of trust is attained. Advanced Customer Segmentation allows you the marketer, to target your marketing and advertising towards these segments who are likely to buy from you than an average market. A marketer can make offers and campaigns that target a specific market using advanced customer segmentation. Personalized offers work best in market segmentation.
Answer:
d. the estimated slope coefficient is more likely to equal the population slope coefficient.
Explanation:
R squared is a statistical measure that measures the closliness of data from regression line. in general a large r squared tends to suggest that the estimated slope coefficient is more likely to equal the population slope coefficient.
