Answer:
feature differentiated products
Explaination:
i just took the quiz
Based on the sales revenue and the net accounts receivable, the receivables turnover ratio is 12 times .
<h3>What is the receivables turnover ratio?</h3>
This can be found as:
= Net sales revenue / Average accounts receivable
Solving give:
= 720,000 / (62,000 + 58,000) / 2
= 720,000 / 60,000
= 12 times
Find out more on receivables turnover ratio at brainly.com/question/27523896.
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Answer:
Step Activities
1 Determine how expensive a car you can afford.
2. Identify the car that meets your needs and wants in terms of size, styling, performance, and safety and obtain online quotes for three target cars.
3. Negotiate the lowest price by getting bids from at least three dealers and hold firm to your target price when selecting the source of your car.
4. Change the oil, rotate the tires, and replace the windshield wipers as needed.
Explanation:
The steps above are arranged to ensure that the next step follows from the last sequentially. The sequence started with making purchase decisions to maintenance activities after the purchase of a car had been completed successfully.
Answer:
sole proprietorship
Explanation:
sole proprietorship is a type of business which is owned and managed by one person and there is no legal difference between owner and business entity itself.
Since in this case business is under the name of Jim, it is sole proprietorship under the law
Answer:
The options for this question are the following:
a. 1
b. 2
c. 0.5
d. 1.5
The correct answer is a. 1
.
Explanation:
Group analysis or grouping is the task of grouping a set of objects in such a way that the members of the same group (called a cluster) are more similar, in some sense or another. It is the main task of exploratory data mining and is a common technique in the analysis of statistical data. It is also used in multiple fields such as machine learning, pattern recognition, image analysis, information search and retrieval, bioinformatics, data compression and graphic computing.
Group analysis is not in itself a specific algorithm, but the task pending solution. Clustering can be done using several algorithms that differ significantly in your idea of what constitutes a group and how to find them efficiently. Classical group ideas include small distances between members of the group, dense areas of the data space, intervals or particular statistical distributions. Clustering, therefore, can be formulated as a multi-objective optimization problem. The appropriate algorithm and the values of the parameters (including values such as the distance function to use, a density threshold or the number of expected groups) depend on the set of data analyzed and the use that will be given to the results. Grouping as such is not an automatic task, but an iterative process of data mining or interactive multi-objective optimization that involves trial and failure. It will often be necessary to pre-process the data and adjust the model parameters until the result has the desired properties.
