diff --git a/education/statistics/Hypothesis Tests.md b/education/statistics/Hypothesis Tests.md
index 06c37c5..81ce7e2 100644
--- a/education/statistics/Hypothesis Tests.md	
+++ b/education/statistics/Hypothesis Tests.md	
@@ -50,11 +50,11 @@ 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.
-If the p-value is less than *5*%, reject the null hypothesis.
-If the p-value is greater than *5*%, fail to reject the null hypothesis.
+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.
 
-(Ch 28, stat 1040)
-## Goodness of fit tests
+(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).
 
 The $\chi^2$ curve does not follow the normal curve. It has a long right hand tail. As the degrees of freedom go up, the curves flatten out, and the hump moves out to the right.