Answer:
Option A
Explanation:
When you combine the costs it will be cheapest:
A - $90
B - $100
C - $110
D - $126
Hope this helps ya out fam!
Brainliest?
~theLocoCoco
Answer:
utility power
Explanation:
In simple words, the location of the house has been said to be in a prominent region, it gives the house a competitive advantage over other units, also the house has been maintained and restructured bu the seller so that it looks more good and healthy.
The subject unit has been restructured in a way that it satisfied all the needs of the buyer, thus, it brings a lot of utility power to the market in respect of its value.
✧・゚: *✧・゚:* *:・゚✧*:・゚✧
Hello!
✧・゚: *✧・゚:* *:・゚✧*:・゚✧
❖ The cover letter should c. introduce you to an employer.
~ ʜᴏᴘᴇ ᴛʜɪꜱ ʜᴇʟᴘꜱ! :) ♡
~ ᴄʟᴏᴜᴛᴀɴꜱᴡᴇʀꜱ
Answer:
Product A because the contribution margin per MH is $23.33
Explanation:
In terms of efficiency, you have to look for the highest outcome with the fewer use of resources. In this case, the resources available are the machines, and the outcome is the profit (margin per unit). Applying the formula: Efficiency producing X (Ex) = [(1 hour of machine hour) / (Product x timed used per unit)]Margin per unit X, and comparing products A and B, you get that producing A is more efficient in terms of profits than producing B, by $10,1 per hour (23,33 - 13,2)
Answer: sentiment analysis software
Explanation: The Content is produced through social networks, through Web forms, through mobile applications. Content is created by your customers, your market, by thought leaders, employees, and other enterprises. They are sharing opinions, ideas, comments, requesting information, expressing concerns, discussing technologies and products and influencing. Valuable information is trending within those conversations, threads, and post .Uncovering and translating social data into tangible insights has become one of the key challenges for Sentiment Analysis technology providers wanting to propose a real social mining solution to their users. The sentiment analysis software is a specialized classification engine used to identify and evaluate subjective patterns and expressions of sentiment within textual content. The analysis is performed at the topic, sentence, and document level and is configured to recognize whether portions of text are factual or subjective and, in the latter case, if the opinion expressed within these pieces of content are positive, negative, mixed, or neutral. The combination of machine learning with natural language processing techniques, the sentiment analysis is one of the most powerful engines available .