commit c0cd66712dce0751976f4ae1ed7cf13c4591eb89
parent 3fd546bc5ad5ac12b7b6a2d87f3592666d7dc010
Author: Andrew <andrewlaack1@gmail.com>
Date: Mon, 22 Jul 2024 17:28:17 -0500
took notes
Diffstat:
4 files changed, 24 insertions(+), 5 deletions(-)
diff --git a/JointProbability.md b/JointProbability.md
@@ -1,10 +1,18 @@
:stats:
# Joint Probability
-Stats D2
+Stats L2 + L6
## Notes
**Definition:** A joint probability is the probability of multiple conditions.
-An example of this is that 48% of voters are in favor of the bill and democrats. This is the joint probability of any given voter being both a democrat and in favor of the bill.
+An example of this is that 48% of voters are in favor of the bill and democrats. This is the joint probability of any given voter being both a democrat and in favor of the bill.
+
+## Joint PMF (L6)
+
+The joint PMF is simply the PMF that represents the probability of joint outcomes.
+
+The joint PMF function, much like normal PMF functions, can be stated as P_{X,Y}(x,y) where X and Y are the joint conditional probabilities and x,y are the joint conditions we are evalulating for.
+
+An important note is that the sum of all x,y for P{X,Y} = 1.
diff --git a/MarginalProbabilities.md b/MarginalProbabilities.md
@@ -1,10 +1,8 @@
:stats:
# Marginal Probabilities
-Stats D2
+Stats L2
## Notes
**Definition:** Marginal probabilities are probabilities that are not conditional upon any other probabilities.
-
-This is in contrast with [[JointProbability.md]] which are ands and [[ConditionalProbabilities.md]] which are ors.
diff --git a/ProbabilityMassFunction.md b/ProbabilityMassFunction.md
@@ -41,3 +41,11 @@ The geometric PMF is **memoryless** in that regardless of the step you start on,
## Conditional (L6)
Conditional PMFs are just PMFs but they have a specified even that occurred. In these instances we simply resize the sample space accordingly and then recalculate probabilities.
+
+## Joint (L6)
+
+See [[JointProbability.md]] for joint PMF information.
+
+## Marginal (L6)
+
+The marginal PMF of X is the P_X(x) that can be found from the joint probability of P_{X,Y}(x,y). Basically, we reverse engineer the probability of a given outcome given the sum of the joint probabilities.
diff --git a/StatisticsAndProbability.md b/StatisticsAndProbability.md
@@ -67,3 +67,8 @@ L6:
- [[Expectation.md]]
- [[Variance.md]]
- [[StandardDeviation.md]]
+ - [[JointProbability.md]]
+L7:
+ - Review
+L8:
+ - [[]]
