
06439632
j
2015d.00872
Rochowicz, John A. jun.
$p$value approximations for $t$tests of hypothesis.
Spreadsheets Educ. 5, No. 3, 20 p., electronic only (2012).
2012
Bond University, Faculty of Business, Gold Coast, Queensland
EN
K75
K95
U75
stochastics
university teaching
quantitative research
spreadsheets
simulation
mathematical statistics
statistical inference
hypothesis testing
parametric $t$tests
$p$values
decision analysis
numerical integration
gamma function
Monte Carlo integration
computer as educational medium
approximations
multiple approaches
$t$distribution
Simpson's rule
NBS approximation
onesample $t$test
twoindependentsamples $t$test
pairedsamples $t$test
http://epublications.bond.edu.au/ejsie/vol5/iss3/5/
Summary: Mathematics can be analyzed in different ways and each method supports the other with the same results. This paper describes a number of approaches for finding the $p$values necessary for making decisions about statistical $t$tests of hypothesis. The concepts of areas under the Student's $t$curve and the mathematical connections between tests of hypothesis,probabilities and areas under a curve are presented. The Excel function TDISTand various approximation techniques from numerical analysis are discussed. Numerical analysis techniques include Simpson's Rule for integration and Monte Carlo integration. Also an approximation from the National Bureau of Standards is provided. Comparisons of results from each method are presented. Numerical approximations are shown to be as important and as accurate as exact solutions.