Total Lines of Code Number of Lines of Code Programmer Written Requiring Edits 4,589 2,780 12,080 3,780 1,890 4,005 Liwel Andrew 23,789 17,962 31,025 26,050 19,586 24,786 Jalme Sherae Binny Roger Dong-Gil Alex 24,030 14,780 30,875 21,546 5,785 1,052 3,872 4,125 Jay Vivek

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Code Churn. Code Churn is a common metric used to measure the efficiency and productivity of software engineers and computer programmers. It’s usually measured as the percentage of a programmer’s code that must be edited over a short period of time. Programmers with higher rates of code churn must rewrite code more often because of errors and inefficient programming techniques. The following table displays sample information for 10 computer programmers.

a. Use the data in the table above and the relative frequency method to determine probabilities that a randomly selected line of code will need to be edited for each programmer.
b. If you randomly select a line of code from Liwei, what is the probability that the line of code will require editing?
c. If you randomly select a line of code from Sherae, what is the probability that the line of code will not require editing?
d. Which programmer has the lowest probability of a randomly selected line of code requiring editing? Which programmer has the highest probability of a randomly selected line of code requiring editing?

Total Lines of Code
Number of Lines of Code
Programmer
Written
Requiring Edits
4,589
2,780
12,080
3,780
1,890
4,005
Liwel
Andrew
23,789
17,962
31,025
26,050
19,586
24,786
Jalme
Sherae
Binny
Roger
Dong-Gil
Alex
24,030
14,780
30,875
21,546
5,785
1,052
3,872
4,125
Jay
Vivek
Transcribed Image Text:Total Lines of Code Number of Lines of Code Programmer Written Requiring Edits 4,589 2,780 12,080 3,780 1,890 4,005 Liwel Andrew 23,789 17,962 31,025 26,050 19,586 24,786 Jalme Sherae Binny Roger Dong-Gil Alex 24,030 14,780 30,875 21,546 5,785 1,052 3,872 4,125 Jay Vivek
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