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2
2
K 2 =
ZbZb
(10)
1
2
2
2
where
Zb are the standard normal deviates equivalent to
transformations of b (skewness) and b (kurtosis) (Armitage and Colton,
1998b). The test-statistic ( K 2 ) has approximately a chi-square distribution
with 2 degrees of freedom under the assumption that two summands [i.e.,
2
Zb and
(
)
()
1
2
Zb are independent and the population is normally
distributed. The assumption of independence cannot be held up for small and
moderate sample sizes. Thus, the fact that K 2 is chi-distributed under the null
hypothesis does not hold true for the most common sample sizes. Test-statistics
of the DAP test is not easy to compute manually, and therefore, statistical
software may be used.
Zb and
(
)
( ]
1
References
Adeloye, A.J. and Montaseri, M. (2002). Preliminary streamflow data analyses prior
to water resources planning study. Hydrological Sciences Journal , 47(5): 679-692.
Armitage, P. and Colton, T. (1998a). Encyclopedia of Biostatistics, Volume 2. Wiley,
New York, pp: 1759-1760.
Armitage, P. and Colton, T. (1998b). Encyclopedia of Biostatistics, Volume 4. Wiley,
New York, pp. 3075-3079.
Bowman, K.O. and Shenton, L.R. (1975). Omnibus test contours for departures from
normality based on b and b 2 . Biometrika , 62: 243-250.
Conover, W.J. (1980). Practical Nonparametric Statistics (Second Edition). John Wiley,
New York, NY.
D'Agostino, R.B. (1986). Tests for the normal distribution. In: R.B. D'Agostino and
M.A. Stephens (editors), Goodness-of-Fit Techniques. Marcel Dekker, New York,
USA.
D'Agostino, R.B., Belanger, A. and D'Agostino Jr., R.B. (1990). Suggestion for using
powerful and informative tests of normality. The American Statistician , 44: 316-
321.
Dixon, W.J. and Massey Jr., F.J. (1983). Introduction to Statistical Analysis. 4 th Edition,
McGraw-Hill, New York, USA.
Filliben, J.J. (1975). The probability plot correlation coefficient test for normality.
Technometrics , 17: 111-117.
Gilbert, R.O. (1987). Statistical Methods for Environmental Pollution Monitoring.
Van Nostrand Reinhold, New York, USA.
GraphPad. (2007). Normality Tests: Use with Caution. http://www.graphpad.com/
library/BiostatsSpecial/article_197.htm (accessed on 14 January 2011).
Jarque, C.M. and Bera, A.K. (1980). Efficient tests for normality, homoscedasticity
and serial independence of regression residuals. Economics Letters , 6(3): 255-259.
Jarque, C.M. and Bera, A.K. (1987). A test for normality of observations and regression
residuals. International Statistical Review , 55(2): 163-172.
Lehmann, E.L. (1999). Elements of Large Sample Theory. Springer, New York.
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