Commit 2ce12bb1 authored by Holger Brandl's avatar Holger Brandl

updated docs

parent 5625c301
......@@ -11,7 +11,7 @@ cd /Users/brandl/Dropbox/projects/datautils/R/rnblight
#git add chi2.md
#git commit -m "initial commit"
mdInput=chi2.md
mdInput=example.md
mdBase=$(basename $mdInput .md)
mv $mdInput ${mdBase}.Rmd
......@@ -22,4 +22,7 @@ EOF
idea .
kscript --idea strip_chunk_results.kts
kscript strip_chunk_results.kts ${mdBase}.md
```
\ No newline at end of file
......@@ -13,25 +13,80 @@ Frequency tests
Proportion Tests
================
```{r}
```r
prop.test(x=333, n=1022, conf.level=0.98)
```
```
##
## 1-sample proportions test with continuity correction
##
## data: 333 out of 1022, null probability 0.5
## X-squared = 123.31, df = 1, p-value < 2.2e-16
## alternative hypothesis: true p is not equal to 0.5
## 98 percent confidence interval:
## 0.2922473 0.3612773
## sample estimates:
## p
## 0.3258317
```
```r
prop.test(x=333, n=1022)
```
```
##
## 1-sample proportions test with continuity correction
##
## data: 333 out of 1022, null probability 0.5
## X-squared = 123.31, df = 1, p-value < 2.2e-16
## alternative hypothesis: true p is not equal to 0.5
## 95 percent confidence interval:
## 0.2973196 0.3556704
## sample estimates:
## p
## 0.3258317
```
From
http://stats.stackexchange.com/questions/60073/confidence-interval-for-difference-between-proportions
The sample size is 34, of which 19 are females and 15 are males. Therefore, the difference in proportions is 0.1176471.
```{r}
```r
19/34 - 15/34
```
```
## [1] 0.1176471
```
```r
prop.test(x=c(19,15), n=c(34,34), correct=FALSE)
```
```
##
## 2-sample test for equality of proportions without continuity
## correction
##
## data: c(19, 15) out of c(34, 34)
## X-squared = 0.94118, df = 1, p-value = 0.332
## alternative hypothesis: two.sided
## 95 percent confidence interval:
## -0.1183829 0.3536770
## sample estimates:
## prop 1 prop 2
## 0.5588235 0.4411765
```
```r
## also works for single proportion
#prop.test(x=c(19), n=c(34), correct=FALSE)
#prop.test(x=c(19,15,20), n=c(34,34,34), correct=FALSE)
```
Also see <http://stat.ethz.ch/R-manual/R-devel/library/stats/html/prop.test.html>
......@@ -48,11 +103,51 @@ Formula:
CI math is detailed out under http://www.statisticslectures.com/topics/ciproportions/
```{r}
```r
prop.test(x=333, n=1022, conf.level=0.98)
```
```
##
## 1-sample proportions test with continuity correction
##
## data: 333 out of 1022, null probability 0.5
## X-squared = 123.31, df = 1, p-value < 2.2e-16
## alternative hypothesis: true p is not equal to 0.5
## 98 percent confidence interval:
## 0.2922473 0.3612773
## sample estimates:
## p
## 0.3258317
```
```r
plot(1:10)
plot(1:10)
```
![plot of chunk unnamed-chunk-3](figure/unnamed-chunk-3-1.png)
```r
prop.test(x=333, n=1022)
```
```
##
## 1-sample proportions test with continuity correction
##
## data: 333 out of 1022, null probability 0.5
## X-squared = 123.31, df = 1, p-value < 2.2e-16
## alternative hypothesis: true p is not equal to 0.5
## 95 percent confidence interval:
## 0.2973196 0.3556704
## sample estimates:
## p
## 0.3258317
```
```r
plot(1:10)
```
Frequency tests
================
* Example: Prop of dieting woman higher than for men?
![](.example_images/fisher_example.png)
```
?fisher.test
```
Proportion Tests
================
```{r}
prop.test(x=333, n=1022, conf.level=0.98)
prop.test(x=333, n=1022)
```
From
http://stats.stackexchange.com/questions/60073/confidence-interval-for-difference-between-proportions
The sample size is 34, of which 19 are females and 15 are males. Therefore, the difference in proportions is 0.1176471.
```{r}
19/34 - 15/34
prop.test(x=c(19,15), n=c(34,34), correct=FALSE)
## also works for single proportion
#prop.test(x=c(19), n=c(34), correct=FALSE)
#prop.test(x=c(19,15,20), n=c(34,34,34), correct=FALSE)
```
Also see <http://stat.ethz.ch/R-manual/R-devel/library/stats/html/prop.test.html>
Nice math introhttps://onlinecourses.science.psu.edu/statprogram/node/164 with t-statistc
Confidence around proportions
-----------------------------
Formula:
> If the samples size n and population proportion p satisfy the condition that np ≥ 5 and n(1 − p) ≥ 5, than the end points of the interval estimate at (1 − α) confidence level is defined in terms of the sample proportion as follows.
![](.example_images/prop_ci.png)
CI math is detailed out under http://www.statisticslectures.com/topics/ciproportions/
```{r}
prop.test(x=333, n=1022, conf.level=0.98)
plot(1:10)
plot(1:10)
prop.test(x=333, n=1022)
plot(1:10)
```
import java.io.File
//val mdFile = File(args[0])
val mdFile = File("/Users/brandl/Dropbox/projects/datautils/R/rnblight/example.md")
//
//var chunkCounter = 0
//var isInChunk = false
//val filtMd = mdFile.readLines().groupBy{ line->
//
// if(line.startsWith("```")) {
// chunkCounter++
// isInChunk = !isInChunk
// }
//
// chunkCounter
//}.filterNot { (_, group) ->
// group.filterNot{it.startsWith("```")}.all { it.startsWith("## ") }
//}
//
//File("result.md").writeText( filtMd.flatMap { it.value }.joinToString("\n"))
val Boolean.int
get() = if (this) 1 else 0
fun <T : Number> List<T>.cumSum(removeNA: Boolean = false): Iterable<Double> {
return drop(1).fold(listOf(first().toDouble()), { list, curVal -> list + (list.last().toDouble() + curVal.toDouble()) })
}
val lines = mdFile.readLines().take(50)
lines.map { it.startsWith("```").int }
lines.map { it.startsWith("```").int }.windowed(2){ (a,b) -> if(a>b) a else b}
lines.map { it.startsWith("```").int }.cumSum().zipWithNext{ a,b -> a}
\ No newline at end of file
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