Websites for Hypothesis Testing

E-learning has become an efficient and widespread
means of education at all levels of human activities. Statistics is no
exception. Unfortunately the main focus in statistics teaching is
usually paid to the substitution in formulas. Suitable websites can
simplify and automate calculations and provide more attention and
time to the basic principles of statistics, mathematization of real-life
situations and following interpretation of results. We now introduce
our own web-site for hypothesis testing. Its didactic aspects, the
technical possibilities of the individual tools, the experience of use
and the advantages or disadvantages are discussed in this paper. This
web-site is not a substitute for common statistical software but should
significantly improve the teaching of statistics at universities.





References:
[1] D. R. Cox, E. J. Snell, Applied Statistics: Principles and Examples. Boca
Raton: Chapnam & Hall/CRC, 1981.
[2] K. A. Carlson, J. R. Winquist, An Introduction to Statistics: An Active
Learning Approachs. Thousand Oaks, Calif.: SAGE Publish., 2014.
[3] A. Grafen, R. Hails, Modern Statistics for the Life Sciences. Oxford:
Oxford University Press, 2002.
[4] R. V. Hogg, J. W. McKean, A. T. Craig, Introduction to Mathematical
Statistics. Upper Side River, New Jersey: Pearson Prentice Hall, 2005.
[5] E. Kaznowska, J. Rogers, A. Usher, “The State of E-Learning in
Canadian Universities, 2011: If Students Are Digital Natives, Why Don't
They Like E-Learning?,” Toronto: Higher Education Strategy
Associates, 2011.
[6] E. L. Lehmann, J. P. Romano, Testing Statistical Hypotheses. New
York: Springer-Verlag, 2005.
[7] J. P. Marques de Sá, Applied Statistics Using SPSS, STATISTICA,
MATLAB and R. Berlin: Springer-Verlag, 2007.
[8] S. Rajpal, S. Singh, A. Bhardwaj, A. Mittal, “E-Learning Revolution:
Status of Educational Programs in India,” in Proc. International
Multiconf. Engineer and Computer Scientists, Hong-Kong.