Update README

README.md

@@ -26,131 +26,14 @@ Here is a list of external code libraries utilized by this library.  The CMake b
 - [FERROR](https://github.com/jchristopherson/ferror)
 - [LINALG](https://github.com/jchristopherson/linalg)
 
-## Example Usage
-The FSTATS library provides many statistical routines.  The example below is a simple regression example illustrating some of the capability of the library and its usage.
-```fortran
-program example
-    use iso_fortran_env
-    use fstats
-    implicit none
-
-    ! Local Variables
-    character, parameter :: tab = achar(9)
-    character, parameter :: nl = new_line('a')
-    integer(int32) :: i
-    real(real64) :: x(31), y(31), coeffs(4), ymodeled(31), residuals(31)
-    type(regression_statistics) :: stats(4)
-
-    ! Define the data
-    x = [ &
-            0.0d0, &
-            0.1d0, &
-            0.2d0, &
-            0.3d0, &
-            0.4d0, &
-            0.5d0, &
-            0.6d0, &
-            0.7d0, &
-            0.8d0, &
-            0.9d0, &
-            1.0d0, &
-            1.1d0, &
-            1.2d0, &
-            1.3d0, &
-            1.4d0, &
-            1.5d0, &
-            1.6d0, &
-            1.7d0, &
-            1.8d0, &
-            1.9d0, &
-            2.0d0, &
-            2.1d0, &
-            2.2d0, &
-            2.3d0, &
-            2.4d0, &
-            2.5d0, &
-            2.6d0, &
-            2.7d0, &
-            2.8d0, &
-            2.9d0, &
-            3.0d0 &
-        ]
-        y = [ &
-            0.577855138260449d0, &
-            0.614883095604222d0, &
-            0.633891127488559d0, &
-            0.718405829701721d0, &
-            0.753668502759107d0, &
-            0.814967857310145d0, &
-            0.861870996499704d0, &
-            0.925100533744381d0, &
-            0.947038018520063d0, &
-            1.025198043343280d0, &
-            1.042142354497610d0, &
-            1.121528566784440d0, &
-            1.177570314994070d0, &
-            1.229237567525370d0, &
-            1.261114062593870d0, &
-            1.296408162551430d0, &
-            1.394353657051120d0, &
-            1.367144391560370d0, &
-            1.428164431435150d0, &
-            1.548944935073270d0, &
-            1.505100149282990d0, &
-            1.560701023751520d0, &
-            1.609113012481530d0, &
-            1.663687366875500d0, &
-            1.707149545456870d0, &
-            1.800935947618110d0, &
-            1.847819988906440d0, &
-            1.884242821675810d0, &
-            1.966174239373140d0, &
-            1.977005266443110d0, &
-            2.034137257154140d0 &    
-        ]
-
-        ! Fit the data
-        call linear_least_squares(3, .true., x, y, coeffs, ymodeled, residuals, stats)
-
-        ! Display the results
-        print '(AF8.5AF8.5AF8.5AF8.5A)', "Model: y = ", &
-            coeffs(1), " + ", &
-            coeffs(2), " x + ", &
-            coeffs(3), " x**2 + ", &
-            coeffs(4), " x**3"
-        
-        ! Illustrate the statistics for each coefficient
-        do i = 1, size(stats)
-            print '(AI0AF6.3AF6.3AF6.3AF6.3)', &
-                "Coefficient ", i, ":" // nl // &
-                tab // "Standard Error: ", stats(i)%standard_error, nl // &
-                tab // "Confidence Interval: +/-", stats(i)%confidence_interval, nl // &
-                tab // "T-Statistic: ", stats(i)%t_statistic, nl // &
-                tab // "P-Value: ", stats(i)%probability
-        end do
-end program
-```
-The following is the output of the program.
-```
-Model: y =  0.55341 +  0.55399 x + -0.05483 x**2 +  0.01185 x**3
-Coefficient 1:
-        Standard Error:  0.015
-        Confidence Interval: +/- 0.031
-        T-Statistic: 36.404
-        P-Value:  0.000
-Coefficient 2:
-        Standard Error:  0.045
-        Confidence Interval: +/- 0.092
-        T-Statistic: 12.417
-Coefficient 3:
-        Standard Error:  0.035
-        Confidence Interval: +/- 0.072
-        T-Statistic: -1.572
-        P-Value:  0.128
-Coefficient 4:
-        Standard Error:  0.008
-        Confidence Interval: +/- 0.016
-        T-Statistic:  1.552
-        P-Value:  0.132
-```
-![](examples/images/Polynomial_Fit_Results.png?raw=true)
+## Capabilities
+- Descriptive Statistics
+- Hypothesis Testing
+- ANOVA
+- Regression
+- Bootstrapping
+- Sampling
+- Special Functions
+- Allan Variance
+- Smoothing
+- Experimental Design