The scatterplot above shows the relationship between the...

The scatterplot above shows the relationship between the number of hours that a group of high school students studied for their biology midterm and their grades on their tests. The line of best fit has also been drawn. If the equation of the line of best fit is written in the form $y=m x+b,$ what is the value of $m+b ?$ $$ \begin{array}{l}{\text { (A) } 55.4} \\ {\text { (B) } 59.0} \\ {\text { (C) } 62.4} \\ {\text { (D) } 65.0}\end{array} $$

The scatterplot above shows the relationship between
the number of hours that a group of high school
students studied for their biology midterm and their
grades on their tests. The line of best fit has also been
drawn. If the equation of the line of best fit is written
in the form $y=m x+b,$ what is the value of $m+b ?$
$$
\begin{array}{l}{\text { (A) } 55.4} \\ {\text { (B) } 59.0} \\ {\text { (C) } 62.4} \\ {\text { (D) } 65.0}\end{array}
$$

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Key Concepts

Combining Linear Parameters

Summing the slope (m) and the y-intercept (b) involves adding two key parameters that characterize a linear equation. This combination can sometimes serve as a simplified metric or provide additional insight into the behavior of the linear model.

Slope-Intercept Form

The slope-intercept form of a linear equation is expressed as y = mx + b, where 'm' represents the slope—a measure of the steepness or rate of change of the line—and 'b' represents the y-intercept, the point where the line crosses the y-axis. This form is fundamental for analyzing linear relationships.

Scatterplot

A scatterplot is a graphical tool used to display the relationship between two quantitative variables. Each point represents an individual data observation, allowing one to visually assess patterns, trends, and potential correlations between the variables.

Line of Best Fit

The line of best fit, also known as the regression line, is drawn through a scatterplot to represent the general trend in the data. It minimizes the overall distance from all the points to the line and is used to predict values and understand the relationship between the two variables.

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