Answer:
$2,560,000
Explanation:
impairment loss = division's book value - division's fair market value = $3,080,000 - $2,320,000 = $760,000
Assets held for sale are no longer depreciated, but they must be recorded at lower value between carrying cost and fair market value. Since the fair market value is lower than carrying value, then an impairment loss results.
loss on discontinued operations = loss from operations 2019 + impairment loss = $1,800,000 + $760,000 = $2,560,000
Answer:
6 times
Explanation:
The formula and the computation of the receivables turnover ratio is shown below:
Account receivable turnover ratio = (Credit sales) ÷ (Average accounts receivable balance)
= ($1,500,000) ÷ ($250,000)
= 6 times
We simply divided the credit sales by the average account receivable balance so that the receivables turnover ratio could arrive
Answer:
E. Labor, capital and management
Explanation:
Productivity refers to efficiency in production which means how much output is produced for available level of inputs. It is measured by output/input ratio.
The variables which determine productivity are labor, capital and management.
Capital refers to the amount of investment an entrepreneur makes in a project. Capital invested determines the resources available.
Labor refers to men employed to produce output. Labor cost refers to the wages paid.
Management refers to carrying out operations effectively so that all factors of production work in synchronization and to ensure that everything is in order.
Answer:
$5600
Explanation:
The amount of depreciation expense for year 1
depreciation under the first year under units of activity method
[ (cost - salvage value) / estimated machine hours ] * actual machine hours worked in the first year
= [(70000 - 14000) / 40000 ] * 4000
= 56000 / 40000 ) * 4000
= 1.4 * 4000 = $5600 ( amount of depreciation expense for year 1 )
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.