<span>Good day! This is [insert name here]. I am interested in applying for a position with your company and I am calling to see if I can make an appointment with human resources to submit my resume. May I know who I should talk to regarding this? Thank you very much!</span>
Answer:
I strongly believe that the correct answer is B. Im going to give an example. if we take into account a company like Honda produces 4000 units, for example Mercedes Benz produces 7000 units, this is very important for welfare economics which tries to put values on consumption.
Explanation:
Answer:
a. $25,650
b. Journal entries
Explanation:
The computation is shown below:
a. The balance of the Allowance for Doubtful Accounts is
= Total account receivable × estimated percentage
= $570,000 × 4.5%
= $25,650
b. The adjusting entry is as follows
Bad Debt Expense $13,650 ($25,650 - $12,000)
To Allowance for Doubtful Accounts $13,650
(Being the bad debt expense is recorded)
c. The adjusting entry is as follows
Bad Debt Expense $26,650 ($25,650 + $1,000)
To Allowance for Doubtful Accounts $26,650
(Being the bad debt expense is recorded)
Answer:
correct option is C. decreases at a decreasing rate.
Explanation:
solution
when an organization gain productivity than its marginal cost will be decreases at a decreasing rate
as here when initial specialization of employee is lead to an significant reduction in the marginal costs though the more specialized people get
and less additional amount is save due to the specialization
so here correct option is C. decreases at a decreasing rate.
Text mining helps companies tap into the massive volume of customer opinions expressed online.
<h3>What is text mining?</h3>
Similar to text analytics, text mining is the technique of extracting high-quality information from text. It is also known as text data mining. It entails "the automatic extraction of information from several written sources to create new, previously unknown information by computer."
The process of converting unstructured text into a structured format with the purpose of identifying significant patterns and fresh insights is known as text mining, also known as text data mining.
Natural language processing is used automatically in text mining to glean insightful information from unstructured material. Text mining automates the process of categorizing texts by sentiment, topic, and intent by converting data into knowledge that computers can comprehend.
To learn more about text mining visit:
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