diff --git a/.obsidian/plugins/obsidian-git/data.json b/.obsidian/plugins/obsidian-git/data.json
index 4bc189e..7b1247f 100644
--- a/.obsidian/plugins/obsidian-git/data.json
+++ b/.obsidian/plugins/obsidian-git/data.json
@@ -2,7 +2,7 @@
   "commitMessage": "vault backup: {{date}}",
   "autoCommitMessage": "vault backup: {{date}}",
   "commitDateFormat": "YYYY-MM-DD HH:mm:ss",
-  "autoSaveInterval": 5,
+  "autoSaveInterval": 1,
   "autoPushInterval": 0,
   "autoPullInterval": 5,
   "autoPullOnBoot": false,
diff --git a/education/statistics/Hypothesis Tests.md b/education/statistics/Hypothesis Tests.md
index 3e3e22f..d1c683d 100644
--- a/education/statistics/Hypothesis Tests.md	
+++ b/education/statistics/Hypothesis Tests.md	
@@ -11,7 +11,7 @@ If an observed value is too many SEs away from the expected value, it is hard to
 	- Null: *x* is *y*. This is often given in the problem
 	- Alternative: If you're being asked to determine if something has changed, you're determining whether or not *x* is equal to. If you're being asked to find the more than, or less than, it's a one sided test.
 2. Then find the SE. This is usually found with: $\frac{SD}{\sqrt{num_{draws}}}$. 
-3. The EV (Expected Value) is usually given as the population %. Then with the above info, you can find the $z$ score with the formula $z = \frac{observed_\% - expected_\%}{SE_\%}$.
+3. The EV (Expected Value) is usually given as the population %. Then with the above info, you can find the $z$ score with the formula $z = \frac{expected_\% - observed_\%}{SE_\%}$.
 4. You can use this $z$ score combined with something like $normalcdf$ to find the amount that is outside of the expected range. If that total amount is less than 5%, than the null hypothesis should be rejected. If that total amount is more than 5%, the difference is too small, and it should not be rejected. 
 Then you can provide a conclusion based off of either the null hypothesis, or the alternative hypothesis.