Answer:
It is easy .8 bits.You have to note this
Answer:
(A) 1
Explanation:
In UNIX the file system the file system is a central part of the operating system. The file system is for storage and retrieval of information. Programs that form the UNIX system also stores information in files.
UNIX file systems supports three files namely: ordinary file, directory files, device files or special files.
If we need to access bytes 2500-2503 it means the bytes are within the third block. So we will need only one access.
Note this is because the file control block (inside) is within the memory. If file control block was not in the memory we would have needed more disk accessses.
When working with a spreadsheet, data analysts can use the CLEAN function to locate specific characters in a string.
<h3>What is the CLEAN Function? </h3>
The CLEAN Function is known to be a tool that is often categorized in the Excel Text functions.
Note that this function tends to delete or remove any kind of non-printable characters from any specified or given text.
Note that As financial analysts, people tend to often import data from a lot of sources and the CLEAN function can help to delete nonprintable characters.
Hence, When working with a spreadsheet, data analysts can use the CLEAN function to locate specific characters in a string.
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When your trying to master the slide layouts you must go to the Slide Layout tab.
A linear regression model is used to show the relationship between variables on a scatter plot
The equation of the linear regression model is: 
and the correlation coefficient is 0.8034
<h3>How to determine the equation of the
linear regression</h3>
The question is incomplete. So, I will make use of a dataset that has the following calculation summary (from a graphing calculator)
- Sum of X = 45
- Sum of Y = 83
- Mean X = 4.5
- Mean Y = 8.3
- Sum of squares (SSX) = 82.5
- Sum of products (SP) = 128.5
- The value of R is 0.8034.
The equation of the linear regression model is:
See attachment for the scatter plot
Read more about linear regression model at:
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