diff --git a/education/statistics/Sampling.md b/education/statistics/Sampling.md
index e38857f..d3bb8d4 100644
--- a/education/statistics/Sampling.md
+++ b/education/statistics/Sampling.md
@@ -6,7 +6,7 @@
 | Quantitative | A numerical value (7, 8, 9) |
 | Population | The entire set of existing units that investigators wish to study |
 | Sample | A portion or subset of the population |
-| Parameter | A number that describes a characteristic of a *population* (*10%* of US senators voted for something) |
+| Parameter | A number that describes a characteristic of an entire *population* (*10%* of US senators voted for something) |
 | Statistic | A number that describes a *sample* characteristic (*71%* of Americans feel that ...) |
 > A global consumer survey reported that 6% of US taxpayers used or owned cryptocurrency in 2020. The US government is interested in knowing if this percentage has increased. The University of Chicago surveys 1,004 taxpayers and finds that 13% have used or owned crypto in the past year (2021)
 
@@ -38,11 +38,12 @@ An ideal sample will represent the whole population.
 ## Percentages
 (Ch 20, stat 1040)
 
-The expected value for a sample percentage equals the population percentage. The standard error for that percentage = `(SE_sum/sample_size) * 100%`
+The expected value for a sample percentage equals the population percentage. The standard error for that percentage = `(SE_sum/sample_size) * 100%`.
 
-To determine by how much the standard error is affected, if `n` is the sample size, the standard error changes by $\frac{1}{\sqrt{n}}$
+To determine by how much the standard error is affected, if $n$ is the proportion that the population changed by, the standard error will change by $\frac{1}{\sqrt{n}}$.
 
 Accuracy in statistics refers to how small the standard error is. A smaller standard error means your data is more accurate.
 
 You can use the below equation to find the percentage standard error of a box model that has ones and zeros. the % of ones and zeros should be represented as a proportion (EG: `60% = 0.6`).
-$$ \sqrt{\frac{(\%\space of\space 1s)(\%\space of\space 0s)}{num_{draws}}} $$(Ch 21, stat 1040)
\ No newline at end of file
+$$ \sqrt{\frac{(\%\space of\space 1s)(\%\space of\space 0s)}{num_{draws}}} $$
+If asked 
\ No newline at end of file