Formatted the description list, added SMC tutorial to verifying.md

content/gui-reference/verifier/verifying.md

@@ -15,40 +15,34 @@ In case the _Over Approximation_ or the _Under Approximation_ options are select
 
 Parameters for statistical model checking can be changed in the [Options](/gui-reference/menu-bar/options/) menu. Various data plots (if available) can be accessed via popup-menu by right-clicking the statistical property. The y-axis always denotes a probability or its density, while x-axis denotes either the variable values limited by the statistical query or a step (transition) count in the model run.
 
-<dl>
+Probability density distribution
+: A histogram created from probability distribution where each bucket is normalized by a bucket width. Useful for comparison of various distributions, potentially with different bucket widths.
 
-<dt>Probability density distribution</dt>
+Probability distribution
+: A histogram created from a frequency histogram where each bucket is normalized by a total number of runs. Useful for assessing a probability of a property being satisfied at a particular moment in time interval.
 
-<dd>A histogram created from probability distribution where each bucket is normalized by a bucket width. Useful for comparison of various distributions, potentially with different bucket widths.</dd>
+Cumulative probability distribution
+: A histogram created by adding up all frequency histogram buckets up to the current bucket and normalized by a total number of runs.
 
-<dt>Probability distribution</dt>
+Confidence Intervals for Probabilities
+: The confidence intervals for probabilities are computed using Clopper-Pearson method (also known as "exact") for binomial distribution for a given level of confidence (1-α). The method is conservative in a sense that it guarantees the minimum coverage of the real probability in (1-α) of cases. In the plots, the estimated confidence is valid only for one bucket at a time (the gathered data is reused to compute each individual bucket).
 
-<dd>A histogram created from a frequency histogram where each bucket is normalized by a total number of runs. Useful for assessing a probability of a property being satisfied at a particular moment in time interval.</dd>
+Confidence Intervals for Mean
+: The confidence intervals for mean estimation are computed using quantiles of Student's t-distribution for a given level of confidence of 1-α. Note that t-distribution approaches the commonly used Normal (Gaussian) distribution when the number of samples is high.
 
-<dt>Cumulative probability distribution</dt>
-
-<dd>A histogram created by adding up all frequency histogram buckets up to the current bucket and normalized by a total number of runs.</dd>
-
-<dt>Confidence Intervals for Probabilities</dt>
-
-<dd>The confidence intervals for probabilities are computed using Clopper-Pearson method (also known as "exact") for binomial distribution for a given level of confidence (1-α). The method is conservative in a sense that it guarantees the minimum coverage of the real probability in (1-α) of cases. In the plots, the estimated confidence is valid only for one bucket at a time (the gathered data is reused to compute each individual bucket).</dd>
-
-<dt>Confidence Intervals for Mean</dt>
-
-<dd>The confidence intervals for mean estimation are computed using quantiles of Student's t-distribution for a given level of confidence of 1-α. Note that t-distribution approaches the commonly used Normal (Gaussian) distribution when the number of samples is high.</dd>
-
-<dt>Frequency histogram</dt>
-
-<dd>The frequency histogram is created by calculating the number of runs satisfying the property at a particular moment in time interval. Useful for calculating the number of runs.</dd>
-
-</dl>
+Frequency histogram
+: The frequency histogram is created by calculating the number of runs satisfying the property at a particular moment in time interval. Useful for calculating the number of runs.
 
 Any plot can be customized from a popup menu by right-clicking on the plot.
 
 Further, the plot labels and titles can be edited and several data sets can be superimposed in one figure by using Plot Composer, accessible from the [Tools](/gui-reference/menu-bar/tools/) menu. It is possible to create several composite plots at a time by invoking Plot Composer multiple times.
 
+See also:
+
+> _UPPAAL SMC tutorial_, **Alexandre David**, **Kim G. Larsen**, **Axel Legay**, **Marius Mikučionis** and **Danny Bøgsted Poulsen**. In: _International Journal on Software Tools for Technology Transfer_ 17, 397–415 (2015). [doi:10.1007/s10009-014-0361-y](https://doi.org/10.1007/s10009-014-0361-y)
+
 An extensive overview and comparison of methods for computing confidence intervals for binomial distribution can be found in the following publications:
 
-> _Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods_, **Ana M. Pires** and **Conceicao Amado**. REVSTAT -- Statistical Journal, Vol.6, No.2, June 2008, pages 165-197.
+> _Interval Estimators for a Binomial Proportion: Comparison of Twenty Methods_, **Ana M. Pires** and **Conceicao Amado**. REVSTAT -- Statistical Journal, Vol.6, No.2, June 2008, pages 165-197. [doi:10.57805/revstat.v6i2.63](https://doi.org/10.57805/revstat.v6i2.63)
 
-> _Interval Estimation for a Binomial Proportion_, **Lawrence D. Brown**, **T. Tony Cai** and **Anirban DasGupta**. Statistical Science, 2001, Vol.16, No.2, pages 101-133.
+> _Interval Estimation for a Binomial Proportion_, **Lawrence D. Brown**, **T. Tony Cai** and **Anirban DasGupta**. Statistical Science, 2001, Vol.16, No.2, pages 101-133. [JSTOR](http://www.jstor.org/stable/2676784)