Documentation for StatisticsReporter

(refs idaholab#16584)
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diff --git a/modules/stochastic_tools/doc/content/source/reporters/StatisticsReporter.md b/modules/stochastic_tools/doc/content/source/reporters/StatisticsReporter.md
@@ -0,0 +1,121 @@
+# StatisticsReporter
+
+!syntax description /Reporters/StatisticsReporter
+
+## Description
+
+The `StatisticsReporter` object computes statistical values for each vector of
+`VectorPostprocessor` (VPP) objects or support values from Reporters.  The results are output in
+values with names based on the input data and the desired statistic calculation. Optionally
+confidence level intervals can be computed.
+
+## Statistics
+
+The statistics to compute are indicated by the [!param](/Reporters/StatisticsReporter/compute)
+parameter, which can contain multiple values as listed below. Note that multiple
+statistical measures can be computed simultaneously by passing in more than one to the input
+parameter.  The current statistical measures the `StatisticsReporter` can compute are:
+
+- +minimum+
+
+  `compute = min`\\
+  Computes the minimum value for the supplied vectors.
+
+- +maximum+
+
+  `compute = max`\\
+  Computes the maximum value for the supplied vectors.
+
+- +sum+
+
+  `compute = sum`\\
+  Computes the sum ($\Sigma$) of the supplied vectors $\vec{v}$, where $N$ is the length of the vector:
+
+  !equation
+  \Sigma = \sum_{i=1}^N{v_i}
+
+- +mean+
+
+  `compute = average`\\
+  Computes the average ($\bar{v}$) of the supplied vectors $\vec{v}$:
+
+  !equation
+  \bar{v} = \frac{\sum_{i=1}^{N}{v_i}}{N}
+
+- +standard deviation+
+
+  `compute = stddev`\\
+  Computes the standard deviation ($\sigma$) of the supplied vectors $\vec{v}$:
+
+  !equation
+  \sigma = \sqrt{\frac{\sum_{i=1}^{N}{(v_i - \bar{v})^2}}{N-1}}
+
+- +L2-Norm+
+
+  `compute = norm2`\\
+  Computes the L2-norm, $|v|_2$ of the supplied vectors $\vec{v}$, this is also known as the
+  Euclidean Norm or the "distance":
+
+  !equation
+  |v|_2 = \sqrt{\sum_{i=1}^{N}{{v_i}^2}}
+
+- +standard error+
+
+  `compute = stderr`\\
+  Computes the standard error ($\sigma_{\bar{v}}$) of the supplied vectors $\vec{v}$:
+
+  !equation
+  \sigma_{\bar{v}} = \frac{\sigma}{\sqrt{N}}
+
+- +ratio+
+
+  `compute = ratio`\\
+  Computes the ratio of the maximum to the minimu of the supplied data.
+
+
+
+## Confidence Levels
+
+Bootstrap confidence level intervals, as defined by [!cite](tibshirani1993introduction), are enabled
+by specifying the desired levels using the
+[!param](/Reporters/StatisticsReporter/ci_levels) parameter and setting
+the method of calculation using the
+[!param](/Reporters/StatisticsReporter/ci_method).
+The levels listed should be in the range (0, 1). For example, the levels 0.05, 0.95 result in the
+computation of the 0.05, 0.95 confidence level intervals.
+
+Enabling the confidence level intervals will compute the intervals for each level and each statistic
+and the result will appear in the same output vector as the associated statistic calculation.
+
+The available methods include the following:
+
+- +percentile+: Percentile bootstrap method as defined in Ch. 13 of [!cite](tibshirani1993introduction).
+
+## Example 1: Statistics
+
+The following input file snippet demonstrates how to compute various statistics using the
+`StatisticsReporter` object.
+
+!listing reporters/statistics/statistics.i block=Reporters
+
+This block results in the following JSON file output.
+
+!listing reporters/statistics/gold/statistics_out.json
+
+
+## Example 2: Confidence Levels
+
+The following input file snippet demonstrates how to compute various statistics and
+confidence levels using the `StatisticsReporter` object.
+
+!listing reporters/bootstrap_statistics/percentile/percentile.i block=Reporters
+
+This block results in the following JSON file.
+
+!listing reporters/bootstrap_statistics/percentile/gold/percentile_out.json
+
+!syntax parameters /Reporters/StatisticsReporter
+
+!syntax inputs /Reporters/StatisticsReporter
+
+!syntax children /Reporters/StatisticsReporter
diff --git a/...stochastic_tools/doc/content/source/vectorpostprocessors/PolynomialChaosData.md b/...stochastic_tools/doc/content/source/vectorpostprocessors/PolynomialChaosData.md
@@ -1 +1,23 @@
-!template load file=stubs/moose_object.md.template name=PolynomialChaosData syntax=/VectorPostprocessors/PolynomialChaosData
+# PolynomialChaosData
+
+!alert construction title=Undocumented Class
+The PolynomialChaosData has not been documented. The content listed below should be used as a starting point for
+documenting the class, which includes the typical automatic documentation associated with a
+MooseObject; however, what is contained is ultimately determined by what is necessary to make the
+documentation clear for users.
+
+!syntax description /VectorPostprocessors/PolynomialChaosData
+
+## Overview
+
+!! Replace these lines with information regarding the PolynomialChaosData object.
+
+## Example Input File Syntax
+
+!! Describe and include an example of how to use the PolynomialChaosData object.
+
+!syntax parameters /VectorPostprocessors/PolynomialChaosData
+
+!syntax inputs /VectorPostprocessors/PolynomialChaosData
+
+!syntax children /VectorPostprocessors/PolynomialChaosData
diff --git a/modules/stochastic_tools/doc/content/source/vectorpostprocessors/Statistics.md b/modules/stochastic_tools/doc/content/source/vectorpostprocessors/Statistics.md
@@ -1,129 +1,4 @@
 # Statistics
 
-!syntax description /VectorPostprocessors/Statistics
-
-## Description
-
-The `Statistics` object computes statistical values for each vector of other
-`VectorPostprocessor` (VPP) objects.  The results are output in vectors that are assigned names
-based on the VPP and vector name (object-vector) and each entry in the vector corresponding
-the the desired statistics and optionally confidence level intervals.
-
-The first column, named `stat_type` and contains an unique integer identifier for the type of
-statistical measure computed and the confidence levels, if computed.
-
-## Statistics
-
-The statistics to compute are indicated by the
-[!param](/VectorPostprocessors/Statistics/compute) parameter, which can contain
-multiple values as listed below. This list also includes the associated numeric identifier
-that is included in the `stat_type` vector output the VPP object.
-
-measures are chosen using the `stats` input parameter.  Note that multiple
-statistical measures can be computed simultaneously by passing in more than one to the `stats` input
-parameter.  The current statistical measures (and their `stat_type` identifier) the
-`StatisticsPostprocessor` can compute are:
-
-- +minimum (0)+
-
-  `compute = min`\\
-  Computes the minimum value for the supplied vectors.
-
-- +maximum (1)+
-
-  `compute = max`\\
-  Computes the maximum value for the supplied vectors.
-
-- +sum (2)+
-
-  `compute = sum`\\
-  Computes the sum ($\Sigma$) of the supplied vectors $\vec{v}$, where $N$ is the length of the vector:
-
-  !equation
-  \Sigma = \sum_{i=1}^N{v_i}
-
-- +mean (3)+
-
-  `compute = average`\\
-  Computes the average ($\bar{v}$) of the supplied vectors $\vec{v}$:
-
-  !equation
-  \bar{v} = \frac{\sum_{i=1}^{N}{v_i}}{N}
-
-- +standard deviation (4)+
-
-  `compute = stddev`\\
-  Computes the standard deviation ($\sigma$) of the supplied vectors $\vec{v}$:
-
-  !equation
-  \sigma = \sqrt{\frac{\sum_{i=1}^{N}{(v_i - \bar{v})^2}}{N-1}}
-
-- +2-Norm (5)+
-
-  `compute = norm2`\\
-  Computes the 2-norm, $|v|_2$ of the supplied vectors $\vec{v}$, this is also known as the
-  Euclidean Norm or the "distance":
-
-  !equation
-  |v|_2 = \sqrt{\sum_{i=1}^{N}{{v_i}^2}}
-
-- +standard error (6)+
-
-  `compute = stderr`\\
-  Computes the standard error ($\sigma_{\bar{v}}$) of the supplied vectors $\vec{v}$:
-
-  !equation
-  \sigma_{\bar{v}} = \frac{\sigma}{\sqrt{N}}
-
-
-## Confidence Levels
-
-Bootstrap confidence level intervals, as defined by [!cite](tibshirani1993introduction), are enabled
-by specifying the desired levels using the
-[!param](/VectorPostprocessors/Statistics/ci_levels) parameter and setting
-the method of calculation using the
-[!param](/VectorPostprocessors/Statistics/ci_method).
-The levels listed should be in the range (0, 0.5]. For example, the levels 0.05, 0.1, and 0.5 provided
-result in the computation of the 0.05, 0.1, 0.5, 0.9, and 0.95 confidence level intervals.
-
-Enabling the confidence level intervals will compute the intervals for each level and each statistic
-and the result will appear in the same output vector as the associated statistic calculation. The
-`stat_type` vector will include decimal values where the ones place indicates the statistic
-computed and the decimal corresponds with the confidence level.
-
-The available methods include the following:
-
-- +percentile+: Percentile bootstrap method as defined in Ch. 13 of [!cite](tibshirani1993introduction).
-
-## Example 1: Statistics
-
-The following input file snippet demonstrates how to compute various statistics using the
-`Statistics` object.
-
-!listing statistics.i block=VectorPostprocessors
-
-This block results in the following CSV file for the "stats" block of the input file. Notice
-the first column corresponds with the numeric identifier for the statistics being computed.
-
-!listing statistics/gold/statistics_out_stats_0001.csv
-
-
-## Example 2: Confidence Levels
-
-The following input file snippet demonstrates how to compute various statistics and
-confidence levels using the `Statistics` object
-
-!listing bootstrap_statistics/percentile/percentile.i block=VectorPostprocessors
-
-This block results in the following CSV file for the "stats" block of the input file. Notice
-the first column corresponds with the numeric identifier for the statistics being computed.
-
-!listing bootstrap_statistics/percentile/gold/percentile_out_stats_0001.csv
-
-!syntax parameters /VectorPostprocessors/Statistics
-
-!syntax inputs /VectorPostprocessors/Statistics
-
-!syntax children /VectorPostprocessors/Statistics
-
-!bibtex bibliography
+!alert warning title=Deprecated Object
+The `Statistics` objects has been replaced by [reporters/StatisticsReporter.md].