diff --git a/SAS/anova.qmd b/SAS/anova.qmd
index 5863ebf4..8387a2af 100644
--- a/SAS/anova.qmd
+++ b/SAS/anova.qmd
@@ -1,5 +1,5 @@
 ---
-title: "linear-models"
+title: "ANOVA"
 ---
 
 ### **Getting Started**
@@ -60,3 +60,5 @@ knitr::include_graphics("../images/linear/sas-ss-type-3.png")
 ```{r, echo=FALSE, fig.align='center', out.width="75%"}
 knitr::include_graphics("../images/linear/sas-ss-type-4.png")
 ```
+
+Reference: [Sum of squares type I, II, and III](http://dwoll.de/rexrepos/posts/anovaSStypes.html)
diff --git a/SAS/summary-stats.qmd b/SAS/summary-stats.qmd
index e2304e80..dc362948 100644
--- a/SAS/summary-stats.qmd
+++ b/SAS/summary-stats.qmd
@@ -1,10 +1,11 @@
 ---
-title: "Deriving Quantiles or Percentiles in SAS"
+title: "Calculating Quantiles (percentiles) in SAS"
 ---
 
 Percentiles can be calculated in SAS using the UNIVARIATE procedure. The procedure has the option `PCTLDEF` which allows for five different percentile definitions to be used. The default is `PCTLDEF=5`, which uses the empirical distribution function to find percentiles.
 
 This is how the 25th and 40th percentiles of `aval` in the dataset `adlb` could be calculated, using the default option for `PCTLDEF`.
+For quantiles, Q1= 25%, Q2=50%, Q3 = 75%, Q4=100%.
 
 ```{r, eval=FALSE}
 proc univariate data=adlb;