diff --git a/2-Regression/3-Linear/README.md b/2-Regression/3-Linear/README.md
index 6a3689852..9e0b95027 100644
--- a/2-Regression/3-Linear/README.md
+++ b/2-Regression/3-Linear/README.md
@@ -50,11 +50,13 @@ We do so since we want to model a line that has the least cumulative distance fr
 > `X` is the 'explanatory variable'. `Y` is the 'dependent variable'. The slope of the line is `b` and `a` is the y-intercept, which refers to the value of `Y` when `X = 0`. 
 >
 >![calculate the slope](images/slope.png)
+>
 > First, calculate the slope `b`. Infographic by [Jen Looper](https://twitter.com/jenlooper)
 >
 > In other words, and referring to our pumpkin data's original question: "predict the price of a pumpkin per bushel by month", `X` would refer to the price and `Y` would refer to the month of sale. 
 >
 >![complete the equation](images/calculation.png)
+>
 > Calculate the value of Y. If you're paying around $4, it must be April! Infographic by [Jen Looper](https://twitter.com/jenlooper)
 >
 > The math that calculates the line must demonstrate the slope of the line, which is also dependent on the intercept, or where `Y` is situated when `X = 0`.