The theme of this volume, dedicated to a great econometrics teacher, is the teaching of econometrics and its pedagogics. In this spirit, this paper revisits some of the basics in the econometrics of panel data and gives my style of teaching this material using tricks from matrix algebra that I found useful to illustrate their value especially for applied researchers who normally want to skip the derivations and focus on applications. I use the Frisch-Waugh-Lovell theorem discussed in Davidson and MacKinnon (1993, p. 19) to explain why the fixed effects estimator can be obtained from the within regression, which is easier to compute and is the standard practice in panel data software. Next, I use a beautiful trick from Wansbeek and Kapteyn (1982) to derive the random effects estimator as a weighted least squares as suggested by Fuller and Battese (1974). The paper then emphasizes that rejecting the Hausman (1978) specification test based on fixed versus random effects is not necessarily an endorsement of the fixed effects estimator as is done regularly in practice. Rejection of the null means that there is misspecification, and Baltagi (2024) provides alternatives to selecting the fixed effects estimator when the Hausman test rejects. Next, the paper demonstrates that for unbalanced panel data with missing observations, things get messy, and the tricks get fancier, and the students complain.