diff --git a/education/statistics/Hypothesis Tests.md b/education/statistics/Hypothesis Tests.md
index 9524e6c..57c249b 100644
--- a/education/statistics/Hypothesis Tests.md	
+++ b/education/statistics/Hypothesis Tests.md	
@@ -21,6 +21,10 @@ Then you can provide a conclusion based off of either the null hypothesis, or th
 | Two tailed test | Use when something is *not equal* to the expected. It's called a two tailed test because the area of significance has two sides. You can find the likelihood of ending up on one side, and the likelihood of ending up on another side, and adding them together (or multiplying by 2 if it's the same on each). |
 ## z tests for averages
 This test will look very similar to a z test for percentages, it still requires that a large, random, sample was given.
+
+## t tests for averages
+This test is used when you have a small sample size (lt 30). 
+The only major differences used with a *t* test is that you use SD+, and 
 ## 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.