It is nonlinear because the increase in the "Total Houses Built" compared to the increase in the "Months Passed" does not show a constant rate of change.
The values in the Total Houses Built column do not increase at a constant additive rate as the Months Passed change. The relationship between the variables is not linear, indicating a nonlinear pattern in the data set.
In a linear relationship, the change in the dependent variable (Total Houses Built) would occur at a constant additive rate for each unit increase in the independent variable (Months Passed).
complete question
The function in the table below shows the relationship between the total number of houses built in an area and the number of months that passed. A two column table with five rows. The first column, Months Passed, has the entries, 0, 3, 4, 8. The second column, Total Houses Built, has the entries 0, 33, 46, 108. Which best describes the data set?
It is nonlinear because the “Total Houses Built” column does not increase at a constant additive rate.
It is nonlinear because the “Months Passed” column does not increase at a constant additive rate.
It is nonlinear because the increase in the “Total Houses Built” compared to the increase in the “Months Passed” does not show a constant rate of change.
It is linear because the increase in the “Total Houses Built” compared to the increase in the “Months Passed” shows a constant rate of change.