{ "_id": "6a103531acfb0bcc41c999a2", "Package": "tcftt", "Type": "Package", "Title": "Two-Sample Tests for Skewed Data", "Version": "0.1.0", "Author": "Huaiyu Zhang, Haiyan Wang", "Maintainer": "Huaiyu Zhang ", "Description": "The classical two-sample t-test works well for the\nnormally distributed data or data with large sample size. The\ntcfu() and tt() tests implemented in this package provide\nbetter type-I-error control with more accurate power when\ntesting the equality of two-sample means for skewed populations\nhaving unequal variances. These tests are especially useful\nwhen the sample sizes are moderate. The tcfu() uses the\nCornish-Fisher expansion to achieve a better approximation to\nthe true percentiles. The tt() provides transformations of the\nWelch's t-statistic so that the sampling distribution become\nmore symmetric. 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