diff --git a/education/statistics/Hypothesis Tests.md b/education/statistics/Hypothesis Tests.md
index 81ce7e2..1a33502 100644
--- a/education/statistics/Hypothesis Tests.md	
+++ b/education/statistics/Hypothesis Tests.md	
@@ -49,10 +49,21 @@ Degrees of freedom ($df$) can be found by subtracting 1 from the sample size. Th
 
 The equivalent of $normalcdf$ for a t test is $tcdf$. This function returns a percentage.
 ## P Value
-The chance of observing at least a sample statistic, or something more extreme, if the null hypothesis is true.
+The *chance of observing at least a sample statistic, or something more extreme*, if the null hypothesis is true.
 If the **p-value is less than *5*%, reject the null** hypothesis, evidence.
 If the **p-value is greater than *5*%, fail to reject** the null hypothesis, not enough evidence.
 
+Investigators should:
+- Summarize the data
+- Say what test was used
+- Report the p-value
+
+Investigators should not:
+- Blindly compare P to 5% or 1%, there are real world factors that change how important this value is. 
+
+### Data Mining/Snooping
+
+
 (Ch 28-29, stat 1040)
 ## Goodness of fit tests ($\chi ^2$) 
 This test is used when you have one qualitative variable with many categories, eg the (color, size, shape) of an (item).