Slight improvement in statistical tests description

docs/what_combine_does/statistical_tests.md

@@ -112,12 +112,12 @@ Under [appropriate conditions](https://arxiv.org/abs/1911.10237), the distributi
 Then, the p-value of the observed test statistic can be calculated from the known form of the expected distribution. 
 This is also true for a number of the other test statistics derived from the likelihood ratio, where [asymptotic approximations have been derived](https://arxiv.org/abs/1007.1727).
 
-Combine provides asymptotic methods, for [limit setting](../../part3/commonstatsmethods/#asymptotic-frequentist-limits) and [significance tests](../../part3/commonstatsmethods/#asymptotic-significances), which make used of these approximations for fast calculations.
+Combine provides asymptotic methods, for [limit setting](../../part3/commonstatsmethods/#asymptotic-frequentist-limits), [significance tests](../../part3/commonstatsmethods/#asymptotic-significances), and [computing confidence intervals](../../part3/commonstatsmethods/#likelihood-fits-and-scans) which make used of these approximations for fast calculations.
 
 In the general case, however, the distribution of the test statistic is not known, and it must be estimated.
 Typically it is estimated by generating many sets of pseudo-data from the model and using the emprirical distribution of the test statistic.
 
-Combine provides methods for [limit setting](../../part3/commonstatsmethods/#computing-limits-with-toys) and [significance tests](../../part3/commonstatsmethods/#computing-significances-with-toys) which use pseudodata generation to estimate the expected test-statistic distributions, and therefore don't depend on the asymptotic approximation.
+Combine also provides methods for [limit setting](../../part3/commonstatsmethods/#computing-limits-with-toys), [significance tests](../../part3/commonstatsmethods/#computing-significances-with-toys), and [computing confidence intervals](../../part3/commonstatsmethods/#feldman-cousins) which use pseudodata generation to estimate the expected test-statistic distributions, and therefore don't depend on the asymptotic approximation.
 Methods are also provided for [generating pseudodata](../../part3/runningthetool/#toy-data-generation) without running a particular test, which can be saved and used for estimating expected distributions.
 
 ### Parameter Estimation using the likelihood ratio