Answer:
The answer is Retain earning (RE).
Explanation:
The profit that they keep to reinvest in the business is reported as retain earning. The part of profit that is not payout as dividend and held for reivestment or any other purpose is included in retian earning and repoted in balance sheet as part of equity above liability section.
Retain earning = Net income - dividend
Retain earning = 35,640 - 3,000 = $ 32,640
A product-process matrix can be used to address the fact that customers often participate in service processes.
This is FALSE.
A customer is a recipient of goods, services, products, or ideas obtained from a seller, vendor, or supplier through financial transactions or in exchange for money or other valuable consideration.
A customer is an individual or business that purchases goods or services from another business. Customers are important because they drive sales. Without them, companies cannot continue to exist.
The definition of customer is a person who purchases products or services at a store, restaurant, or another retail establishment. An example of a customer is someone who goes to an electronics store and buys a television. (informal) A person, especially a person, who interacts with others in some way.
Learn more about customer here:brainly.com/question/12831236
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Answer:
The correct answer is 16 utils.
Explanation:
Amount spent by Rick to get utility of 8 = $6*2 + $3 * 4 = $24
$48/ $24 = 2
$48 will give Rick 2 sets of products combination that give him utility of 8.
At his utility-maximizing point, Rick's utility is 2* 8 = 16 utils.
Answer:
Supervised and Unsupervised Learning:
a. Unsupervised learning
b. Supervised learning
3. Supervised learning
4. Unsupervised learning
Explanation:
The key difference between supervised machine learning and unsupervised machine learning is that with supervised machine learning there is a training dataset (labeled data) on which the algorithm is trained to predict patterns. With unsupervised machine learning on the other hand, there is no training data. So, the algorithm discovers patterns on itself without reference to another labeled data or training dataset.
1. revenue 2. income 3. graph 4. equity 5. balance sheet 6. income taxes
