Answer:
Explanation:
Formulas!D11: =C11*0.0675
4 / 7 (57.1%)
Feedback:
[-2] The formula in cell D11 does not reference the sales tax rate
[-1] The tax rate reference is not absolute
Copy the formula you used in cell D11 down to calculate the sales tax amount for the remaining transactions.
1 / 1 (100.0%)
Feedback:
Construct a formula in cell E11 to calculate the total amount for transaction 578. Be sure to appropriately reference the transaction amount in cell C11 and the sales tax amount in cell D11 so that you can reuse your formula to calculate the total for the remaining transactions.
Formulas!E11: =SUM(C11:D11)
6 / 6 (100.0%)
Feedback:
Copy the formula you used in cell E11 down to calculate the total for the remaining transactions.
2 / 2 (100.0%)
Feedback:
Use the SUM function to calculate the “Grand Total” in for all transactions in cell E24.
Formulas!E24: =SUM(E11:E23)
4 / 4 (100.0%)
Answer:.doc and .docx - Microsoft Word file.
.odt - OpenOffice Writer document file.
.pdf - PDF file.
.rtf - Rich Text Format.
.tex - A LaTeX document file.
.txt - Plain text file.
.wpd - WordPerfect documen
Explanation:
Answer:
Yes
Explanation:
Being online is a different world... They are communist in real life.
<span>While you are working with a document using a program such as wordpad, the document is stored in .txt format</span>
Answer and Explanation:
The sequential data or sequence data is described as data that come in an ordered sequence. It may also be termed data that is produced from tasks that occurs in sequential order The sequential pattern mining is a critical subject in data mining that has do with applying sequential data to derive a statistically relevant pattern from it.
Sequential pattern mining is a part of data mining. Data mining involves utilizing data from databases to understand and make decisions that better the organization or society as a whole based on this. Common data mining tasks include: clustering, classification, outlier analysis, and pattern mining.
Pattern mining is a kind of data mining task that involves explaining data through finding useful patterns from data in databases. Sequential pattern mining is pattern mining that uses sequential data as a source of data in finding data patterns. Sequential pattern mining applies various criteria(which maybe subjective) in finding "subsequence" in data. Criteria could be :frequency, length, size, time gaps, profit etc. Sequential pattern mining is commonly applicable in reality since a sizeable amount of data mostly occur in this form. A popular type of sequential data is the time series data.