Chi-squared test for single sample variance in r

Asked Jun 10 '21 at 18:18

Active Jun 10 '21 at 18:40

Viewed 120 times

I am supposed to make a single sample test and answer with a<0.05 about the variance of the sample. But I'm not really sure how to get it from single sample. I tried something like this

variance <- 0.0001
sample <- c(8.99, 9.01, 8.98, 9.00, 9.01)
alpha <- 0.05
X <- t.test(x = sample, conf.level = 1 - alpha, alternative = "two.sided")
sum((sample[1:5] - X$estimate)^2) < variance

It returnes TRUE, but I don't think that's the right approach. From what I've seen I need to somehow use chisq.test(). I used it on the sample and got

    Chi-squared test for given probabilities

data:  sample
X-squared = 7.5572e-05, df = 4, p-value = 1

And I'm not sure what to get out of it. Does that mean that it's 100% likely because p-value is equal to one? Or did I get something wrong? Any help would be appreciated!

edited Jun 10 '21 at 18:40

asked Jun 10 '21 at 18:18

WPHakoon

You have a typo in `X$estimate`. – Rui Barradas Jun 10 '21 at 18:31
@RuiBarradas Thanks, fixed that – WPHakoon Jun 10 '21 at 18:32
1

More importantly, you say you need to use `chisq.test` but haven't said *what* do you want to test. (The `t.test` is testing whether the true mean is 0, right?) – Rui Barradas Jun 10 '21 at 18:33
@RuiBarradas My bad, thought i said it in the post, i need to check if variance of the sample is 0.0001, as in the code – WPHakoon Jun 10 '21 at 18:40
`EnvStats::varTest(sample, "two.sided", sigma.squared = variance)` is what you're lookung for. – Rui Barradas Jun 10 '21 at 21:56

Chi-squared test for single sample variance in r

0 Answers0