The image provided shows a scatterplot with data about phone sales over a 7-month period. The line of best fit passes through two points: $(0, 105)$ and $(7, 112.7)$. From this information, we can determine the equation of the line of best fit.

Step-by-Step Calculation:

1. Find the slope of the line ($m$):
   The slope formula is: $m = \frac{y_2 - y_1}{x_2 - x_1}$ Where $(x_1, y_1) = (0, 105)$ and $(x_2, y_2) = (7, 112.7)$. $m = \frac{112.7 - 105}{7 - 0} = \frac{7.7}{7} = 1.1$ So, the slope of the line is $m = 1.1$.

2. Find the equation of the line using the point-slope form: The point-slope form is: $y - y_1 = m(x - x_1)$ Using the point $(0, 105)$ and $m = 1.1$: $y - 105 = 1.1(x - 0)$ Simplifying: $y = 1.1x + 105$ This is the equation of the line of best fit.

The equation represents the trend of phone sales over time, where the slope indicates that for each month, approximately 1.1 more phones are sold compared to the previous month.

Would you like further clarification or more details?

Follow-up questions:

1. How do you calculate the slope of a line given two points?
2. What does the slope represent in this context?
3. How can you use the equation of the line to predict future phone sales?
4. How do we know the line is the best fit for the scatterplot?
5. What is the significance of the y-intercept in this equation?

Tip: The slope of a line describes how fast the dependent variable (phone sales) changes as the independent variable (time in months) increases.