Question

a software developer is looking for ways to predict how many bugs will appear in future projects. he used a bug - tracking database to analyze several recent projects. from the database, he recorded the number of lines of code for each project, x. he also looked up the number of the number of lines of code for each project, x. he also looked up the number of bugs that had been found in each projects code, y. lines of code bugs 510 211 6,253 107 9,123 200 10,041 147 10,986 259 11,905 208 12,838 333 19,125 428 the correct least squares regression line for the data set is: y = 0.014x + 98.546 use it to complete the following sentence: for each additional line of code, the least squares regression line predicts more bugs would be found in that project.

Explanation:

Step1: Identify the slope of regression line

The regression line is $y = 0.014x+98.546$, and in the linear - regression equation $y = mx + b$, $m$ is the slope.

Step2: Interpret the slope

The slope $m = 0.014$ represents the change in $y$ (number of bugs) for a unit change in $x$ (number of lines of code). So for each additional line of code ($x$ increases by 1), the value of $y$ (number of bugs) increases by 0.014 according to the regression line.

Answer:

0.014