Question

The arm span and foot length were measured (in

centimeters) for each of the 19 students in a statistics
class. The results are displayed in the scatterplot.
Arm Span vs. Foot Length
Foot Length (cm)
29
27
23
21
●
●
19
155 160 165 170 175 180 185 190 195
Arm Span (cm)
The equation ý = -7.61 +0.19x is called the least-
squares regression line because it
O passes through each data point.
Ominimizes the sum of the squared residuals.
Omaximizes the sum of the squared residuals.
O is least able to make accurate predictions for the
data.

Answer 1

Answer: The correct answer is:

The equation ý = -7.61 +0.19x is called the least-squares regression line because it minimizes the sum of the squared residuals.

Step-by-step explanation:

The least-squares regression line is a line that represents the best linear approximation of the relationship between two variables. It is called "least-squares" because it minimizes the sum of the squared residuals, which are the differences between the observed values and the predicted values from the regression line.

In this case, the scatterplot shows the relationship between arm span and foot length for 19 students in a statistics class. The equation ý = -7.61 +0.19x is the equation of the least-squares regression line for this data set. This means that it is the line that best fits the data by minimizing the sum of the squared residuals.

Therefore, the correct answer is that the equation ý = -7.61 +0.19x is called the least-squares regression line because it minimizes the sum of the squared residuals.

Step-by-step explanation: