Statistics::PointEstimation Statistics::PointEstimation is a Perl module for computing confidence intervals in parameter estimation.
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Perl module intervals confidence intervals parameter estimation confidence

Statistics::PointEstimation Description

Statistics::PointEstimation is a Perl module for computing confidence intervals in parameter estimation. Statistics::PointEstimation is a Perl module for computing confidence intervals in parameter estimation with Student's T distribution.Statistics::PointEstimation::Sufficient - Perl module for computing the confidence intervals using sufficient statisticsSYNOPSIS # example for Statistics::PointEstimation use Statistics::PointEstimation; my @r=(); for($i=1;$iset_significance(95); #set the significance(confidence) level to 95% $stat->add_data(@r); $stat->output_confidence_interval(); #output summary $stat->print_confidence_interval(); #output the data hash related to confidence interval estimation #the following is the same as $stat->output_confidence_interval(); print "Summary from the observed values of the sample:n"; print "tsample size= ", $stat->count()," , degree of freedom=", $stat->df(), "n"; print "tmean=", $stat->mean()," , variance=", $stat->variance(),"n"; print "tstandard deviation=", $stat->standard_deviation()," , standard error=", $stat->standard_error(),"n"; print "t the estimate of the mean is ", $stat->mean()," +/- ",$stat->delta(),"nt", " or (",$stat->lower_clm()," to ",$stat->upper_clm," ) with ",$stat->significance," % of confidencen"; print "t t-statistic=T=",$stat->t_statistic()," , Prob >|T|=",$stat->t_prob(),"n"; #example for Statistics::PointEstimation::Sufficient use strict; use Statistics::PointEstimation; my ($count,$mean,$variance)=(30,3.996,1.235); my $stat = new Statistics::PointEstimation::Sufficient; $stat->set_significance(99); $stat->load_data($count,$mean,$variance); $stat->output_confidence_interval(); $stat->set_significance(95); $stat->output_confidence_interval();Statistics::PointEstimationThis module is a subclass of Statistics::Descriptive::Full. It uses T-distribution for point estimation assuming the data is normally distributed or the sample size is sufficiently large. It overrides the add_data() method in Statistics::Descriptive to compute the confidence interval with the specified significance level (default is 95%). It also computes the t-statistic=T and Prob>|T| in case of hypothesis testing of paired T-tests.Statistics::PointEstimation::SufficientThis module is a subclass of Statistics::PointEstimation. Instead of taking the real data points as the input, it will compute the confidence intervals based on the sufficient statistics and the sample size inputted. To use this module, you need to pass the sample size, the sample mean , and the sample variance into the load_data() function. The output will be exactly the same as the Statistics::PointEstimation Module.Requirements:· Perl Requirements: · Perl

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