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The efficiencies of statistical methods (i.e., EPFM, MSDM, MOM and LSRM) at different locations are furnished in Tables 7, 8, 9, 10.
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Although several promising methods are available, the relevant issues of study design and data analysis for detecting interactions including sample size for a desirable power and the efficiency of statistical methods have not been well explored.
In statistical analysis, for judgment of statistical methods to each other and to find out the efficiency of the methods, six statistical tools, i.e., relative percentage error (RPE), root mean square error (RMSE), mean percentage error (MPE), mean absolute percentage error (MAPE), Chi square error (χ 2), and analysis of variance or efficiency of the method (R 2) were used.
The raw survey data permit the use of statistical methods to explain and predict how individuals vote.
The contrast of statistical methods is compared through relative percentage error, root mean square error, mean percentage error, mean absolute percentage error, Chi-square error and analysis of variance (or) efficiency of the methods used.
BS provided oversight of statistical methods.
Special issue of Statistical Methods in Medical Research.
The efficiency of several statistical methods used for this purpose has previously been evaluated (Romualdi et al. 2001).
The correctness, robustness, efficiency and relevance [ 7] of the statistical methods reported in the sample papers were assessed using a yes or no assignment for each characteristic.
The test results of four statistical methods and standings of the methods according to their performance and efficiency in evaluation of wind data is summarized in Table 11.
Tells about critique of his statistical methods..
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