# diff and diff with multiple time periods - test parallel trend assumption

I am performing this resgression: $$y_{it} = \beta_{0} + \beta_{1}\text{Treat}_{i} + \sum_{j \neq k} \lambda_{j} \text{Year}_{t=j} + \sum_{j \neq k} \delta_j \left( \text{Treat}_i \cdot \text{Year}_{t=j} \right) + X_{it}'\gamma + \epsilon_{it}.$$

Yit - is a binary variable time periods t=1,2,...,k,...,T
the treatment happens between k and k+1 (so time k is my last pre-treatment period).

My question is how to present to parallel trend assumption.
I understand that there are 2 methods:
1. If coefficients δ before treatment are essentially zero. (If I get this right the 2 option are that they are equal or close to 0 and statistically significant or they are not equal to 0 and not statistically significant).
2. Run the regression separately for the treatment and control groups. Instead of a series of treat*quarter coefficients, we have just quarter coefficients for each group, and then plot those on the same graph.

Do I understand it correctly? what is the proper way to present it?

would love any help, Thank you!