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. Total Lines of Code Number of Lines of Code Programmer Written Requiring Edits Liwei 24,830 5,432 Andrew 16,210 2,114 Jaime 29,750 11,596 Sherae 26,934 4,667 Binny 22,536 5,689 Roger 24,900 2,310 Dong-Gil 21,369 2,650 Alex 16,842 4,505 Jay 31,658 3,657 Vivek 23,887 4,321 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. Round your answers to four decimal places. Programmer Probability Liwei Andrew Jaime Sherae Binny Roger Dong-Gil Alex Jay Vivek If you randomly select a line of code from Liwei, what is the probability that the line of code will require editing? Round your answer to four decimal places. If you randomly select a line of code from Sherae, what is the probability that the line of code will not require editing? Round your answer to four decimal places.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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.

	Total Lines of Code	Number of Lines of Code
Programmer	Written	Requiring Edits
Liwei	24,830	5,432
Andrew	16,210	2,114
Jaime	29,750	11,596
Sherae	26,934	4,667
Binny	22,536	5,689
Roger	24,900	2,310
Dong-Gil	21,369	2,650
Alex	16,842	4,505
Jay	31,658	3,657
Vivek	23,887	4,321

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. Round your answers to four decimal places.
1. Programmer Probability
  
  Liwei
  
  Andrew
  
  Jaime
  
  Sherae
  
  Binny
  
  Roger
  
  Dong-Gil
  
  Alex
  
  Jay
  
  Vivek
If you randomly select a line of code from Liwei, what is the probability that the line of code will require editing? Round your answer to four decimal places.
If you randomly select a line of code from Sherae, what is the probability that the line of code will not require editing? Round your answer to four decimal places.

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Step 1

Given

Programmer	Total lines of code Written	Number of lines of code Requiring Edits
Liwei	24,830	5,432
Andrew	16,210	2,114
Jaime	29,750	11,596
Sherae	26,934	4,667
Binny	22,536	5,689
Roger	24,900	2,310
Dong-Gil	21,369	2,650
Alex	16,842	4,505
Jay	31,658	3,657
Vivek	23,887	4,321

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