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			127 lines
		
	
	
		
			4.5 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
		
		
			
		
	
	
			127 lines
		
	
	
		
			4.5 KiB
		
	
	
	
		
			C++
		
	
	
	
	
	
|  | // students_t_example2.cpp
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|  | 
 | ||
|  | // Copyright Paul A. Bristow 2006.
 | ||
|  | // Use, modification and distribution are subject to the
 | ||
|  | // Boost Software License, Version 1.0.
 | ||
|  | // (See accompanying file LICENSE_1_0.txt
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|  | // or copy at http://www.boost.org/LICENSE_1_0.txt)
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|  | 
 | ||
|  | // Example 2 of using Student's t
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|  | 
 | ||
|  | // A general guide to Student's t is at
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|  | // http://en.wikipedia.org/wiki/Student's_t-test
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|  | // (and many other elementary and advanced statistics texts).
 | ||
|  | // It says:
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|  | // The t statistic was invented by William Sealy Gosset
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|  | // for cheaply monitoring the quality of beer brews.
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|  | // "Student" was his pen name.
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|  | // Gosset was statistician for Guinness brewery in Dublin, Ireland,
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|  | // hired due to Claude Guinness's innovative policy of recruiting the
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|  | // best graduates from Oxford and Cambridge for applying biochemistry
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|  | // and statistics to Guinness's industrial processes.
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|  | // Gosset published the t test in Biometrika in 1908,
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|  | // but was forced to use a pen name by his employer who regarded the fact
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|  | // that they were using statistics as a trade secret.
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|  | // In fact, Gosset's identity was unknown not only to fellow statisticians
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|  | // but to his employer - the company insisted on the pseudonym
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|  | // so that it could turn a blind eye to the breach of its rules.
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|  | 
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|  | // The Students't distribution function is described at
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|  | // http://en.wikipedia.org/wiki/Student%27s_t_distribution
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|  | 
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|  | #include <boost/math/distributions/students_t.hpp>
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|  |    using boost::math::students_t;  // Probability of students_t(df, t).
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|  | 
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|  | #include <iostream>
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|  |    using std::cout; | ||
|  |    using std::endl; | ||
|  | #include <iomanip>
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|  |    using std::setprecision; | ||
|  |    using std::setw; | ||
|  | #include <cmath>
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|  |    using std::sqrt; | ||
|  | 
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|  | // This example of a one-sided test is from:
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|  | //
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|  | // from Statistics for Analytical Chemistry, 3rd ed. (1994), pp 59-60
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|  | // J. C. Miller and J. N. Miller, Ellis Horwood ISBN 0 13 0309907.
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|  | 
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|  | // An acid-base titrimetric method has a significant indicator error and
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|  | // thus tends to give results with a positive systematic error (+bias).
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|  | // To test this an exactly 0.1 M solution of acid is used to titrate
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|  | // 25.00 ml of exactly 0.1 M solution of alkali,
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|  | // with the following results (ml):
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|  | 
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|  | double reference = 25.00; // 'True' result.
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|  | const int values = 6; // titrations.
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|  | double data [values] = {25.06, 25.18, 24.87, 25.51, 25.34, 25.41}; | ||
|  | 
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|  | int main() | ||
|  | { | ||
|  |    cout << "Example2 using Student's t function. "; | ||
|  | #if defined(__FILE__) && defined(__TIMESTAMP__) && defined(_MSC_FULL_VER)
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|  |    cout << "  " << __FILE__ << ' ' << __TIMESTAMP__ << ' '<< _MSC_FULL_VER; | ||
|  | #endif
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|  |    cout << endl; | ||
|  | 
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|  |    double sum = 0.; | ||
|  |    for (int value = 0; value < values; value++) | ||
|  |    { // Echo data and calculate mean.
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|  |       sum += data[value]; | ||
|  |       cout << setw(4) << value << ' ' << setw(14) << data[value] << endl; | ||
|  |    } | ||
|  |    double mean = sum /static_cast<double>(values); | ||
|  |    cout << "Mean = " << mean << endl; // 25.2283
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|  | 
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|  |    double sd = 0.; | ||
|  |    for (int value = 0; value < values; value++) | ||
|  |    { // Calculate standard deviation.
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|  |       sd +=(data[value] - mean) * (data[value] - mean); | ||
|  |    } | ||
|  |    int degrees_of_freedom = values - 1; // Use the n-1 formula.
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|  |    sd /= degrees_of_freedom; // == variance.
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|  |    sd= sqrt(sd); | ||
|  |    cout << "Standard deviation = " << sd<< endl; // = 0.238279
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|  | 
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|  |    double t = (mean - reference) * sqrt(static_cast<double>(values))/ sd; //
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|  |    cout << "Student's t = " << t << ", with " << degrees_of_freedom << " degrees of freedom." << endl; // = 2.34725
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|  | 
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|  |    cout << "Probability of positive bias is " << cdf(students_t(degrees_of_freedom), t) << "."<< endl; // =  0.967108.
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|  |    // A 1-sided test because only testing for a positive bias.
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|  |    // If > 0.95 then greater than 1 in 20 conventional (arbitrary) requirement.
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|  | 
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|  |    return 0; | ||
|  | }  // int main()
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|  | 
 | ||
|  | /*
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|  | 
 | ||
|  | Output is: | ||
|  | 
 | ||
|  | ------ Build started: Project: students_t_example2, Configuration: Debug Win32 ------ | ||
|  | Compiling... | ||
|  | students_t_example2.cpp | ||
|  | Linking... | ||
|  | Autorun "i:\boost-06-05-03-1300\libs\math\test\Math_test\debug\students_t_example2.exe" | ||
|  | Example2 using Student's t function.   ..\..\..\..\..\..\boost-sandbox\libs\math_functions\example\students_t_example2.cpp Sat Aug 12 16:55:59 2006 140050727 | ||
|  |    0          25.06 | ||
|  |    1          25.18 | ||
|  |    2          24.87 | ||
|  |    3          25.51 | ||
|  |    4          25.34 | ||
|  |    5          25.41 | ||
|  | Mean = 25.2283 | ||
|  | Standard deviation = 0.238279 | ||
|  | Student's t = 2.34725, with 5 degrees of freedom. | ||
|  | Probability of positive bias is 0.967108. | ||
|  | Build Time 0:03 | ||
|  | Build log was saved at "file://i:\boost-06-05-03-1300\libs\math\test\Math_test\students_t_example2\Debug\BuildLog.htm" | ||
|  | students_t_example2 - 0 error(s), 0 warning(s) | ||
|  | ========== Build: 1 succeeded, 0 failed, 0 up-to-date, 0 skipped ========== | ||
|  | 
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|  | */ | ||
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