Search Results
| Search type | Search syntax |
|---|---|
| Tags | [tag] |
| Exact | "words here" |
| Author |
user:1234 user:me (yours) |
| Score |
score:3 (3+) score:0 (none) |
| Answers |
answers:3 (3+) answers:0 (none) isaccepted:yes hasaccepted:no inquestion:1234 |
| Views | views:250 |
| Code | code:"if (foo != bar)" |
| Sections |
title:apples body:"apples oranges" |
| URL | url:"*.example.com" |
| Saves | in:saves |
| Status |
closed:yes duplicate:no migrated:no wiki:no |
| Types |
is:question is:answer |
| Exclude |
-[tag] -apples |
| For more details on advanced search visit our help page | |
Results tagged with r
Search options not deleted
user 93623
Use this tag for any *on-topic* question that (a) involves `R` either as a critical part of the question or expected answer, & (b) is not *just* about how to use `R`.
1
vote
Accepted
How to calculate p-value when comparing the percentage similarity of matrices in R
Assuming that the data you want to analyse is like the data you've synthesised, that is, a bernoulli process, I think you can use a simple binomial test.
Imagine you have two coins. You've tested them …
- 471
2
votes
Missing observations within nested random effects
Short answer: Yes, at least for the species in question.
Long answer: What do you mean with "missing"?
To answer this I thought it fitting to make a simulation and a few scenarios of why data might go …
- 471
4
votes
Regression with a 0-1 variable. Should be the same as running a t-test, but I get a differen...
# x 1.34139 0.56629 2.3687 0.01981 *
# ---
# Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#
# Residual standard error: 2.8292 on 98 degrees of freedom
# Multiple R-squared … : 0.054154, Adjusted R-squared: 0.044503
# F-statistic: 5.611 on 1 and 98 DF, p-value: 0.01981
#
t.test(y ~ x, data=dtf, var.equal=TRUE)
#
# Two Sample t-test
#
# data: y by x
# t = -2.36875 …
- 471
4
votes
1
answer
132
views
Repeated catch–mark–release (urn problem)
For any fellow R fiends and others interested, the above sequence was generated like this:
set.seed(1)
pool <- rep(0, 64)
capture <- vector()
for (i in 1:40) {
capture[i] <- sample(pool, 1)
if (capture …
- 471
0
votes
Two- Sample T test on Employment Data
The p-value is correct, the error lies in your method. If we plot the time series I think this will become obvious.
# Data
employees <- read.csv("https://fred.stlouisfed.org/graph/fredgraph.csv?i …
- 471