From f049604809eef91dc02811c67ecfb03d578307c9 Mon Sep 17 00:00:00 2001 From: zleyyij Date: Thu, 25 Jan 2024 14:00:30 -0700 Subject: [PATCH] vault backup: 2024-01-25 14:00:30 --- education/statistics/Sampling.md | 9 ++++++++- 1 file changed, 8 insertions(+), 1 deletion(-) diff --git a/education/statistics/Sampling.md b/education/statistics/Sampling.md index d3bb8d4..5e0e628 100644 --- a/education/statistics/Sampling.md +++ b/education/statistics/Sampling.md @@ -38,6 +38,8 @@ An ideal sample will represent the whole population. ## Percentages (Ch 20, stat 1040) +Throughout this chapter, percentages are often represented by referencing a box model of 1s and 0s, where 1s are datapoints that *are* counted, and 0s are datapoints that are not counted. + 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 proportion that the population changed by, the standard error will change by $\frac{1}{\sqrt{n}}$. @@ -46,4 +48,9 @@ Accuracy in statistics refers to how small the standard error is. A smaller stan 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`). $$ \sqrt{\frac{(\%\space of\space 1s)(\%\space of\space 0s)}{num_{draws}}} $$ -If asked \ No newline at end of file +If asked if an observed % is reasonable, you can calculate the z score, and if the z score is more than 2-3 standard deviations away. + +(Ch 23, stat 1040) + + +