1
$\begingroup$

I have two data sets of hourly measurements from two different time periods. During each time period, the values drop below a given threshold for different amounts of time.

I would like to develop a statistical basis for determining if the amount of time spent below the threshold during period 1 is significantly different from the amount of time spent below the threshold during period 2.

For example, if the temperature drops below 10 deg C for 15 hours during one week and for 22 hours during another week, the difference in the number of hours below 10 deg C would be 7.

Are there any statistical methods to determine if this difference of 7 hours is a "significant" amount of time? (among the 168 hours that are in a week)

$\endgroup$
0
$\begingroup$

Yes, this is the test for equality of proportions $p_1, p_2$ in two populations given samples of sizes $n_1, n_2$ respectively.

Null is $H_0 : p_1-P_2 =0 $

Alternative is $H_A: p_1 \neq p_2 $ (two-tailed)

The z statistic is

$z= \frac {p_1 -p_2}{\sqrt {p'(1-p')(\frac {1}{n_1}+\frac {1}{n_2})}}$

Where $p$ is the pooled proportion ; $p= \frac {s_1+s_2}{n_1+n_2}$; $s_1,s_2$ are the "successes" and $n_1,n_2$ are the respective number of trials.

https://onlinecourses.science.psu.edu/stat414/node/268/

EDIT: For the sake of completeness, there is another type of test when you have contingency tables ( included in link), but this is not your case.

| cite | improve this answer | |
$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.