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Statistics course and homework discussion. Elementary statistics.enFri, 20 Oct 2017 05:11:15 GMTvBulletin60http://www.talkstats.com/images/misc/rss.pngStatistics Help @ Talk Stats Forum - Statistics
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One or two tailed test?
http://www.talkstats.com/showthread.php/70415-One-or-two-tailed-test?goto=newpost
Thu, 19 Oct 2017 14:52:01 GMTHi, I am currently struggling to decide whether the following problem requires a one or two tailed t test for a hypothesis test. I have uploaded a...Hi, I am currently struggling to decide whether the following problem requires a one or two tailed t test for a hypothesis test. I have uploaded a photo of the data used if needed.

'Test the individual significance of the explanatory variable. You should decide on an appropriate t-test (one tailed or two tailed) and explain why you've chosen this test.

Thanks in advance :) .

]]>StatisticsTomAhttp://www.talkstats.com/showthread.php/70415-One-or-two-tailed-testAppropriate Bonferroni correction
http://www.talkstats.com/showthread.php/70414-Appropriate-Bonferroni-correction?goto=newpost
Thu, 19 Oct 2017 14:32:13 GMTI'm comparing two groups of patients using several 3x2 and 4x2 contingency tables (for different sublevels of chemotherapy for instance). Question is how much do I need to adjust P value using Bonferroni correction (for 4 or 6 comparisons when analyzing 2x4 table, for 5 or 10 comparisons when analyzing 5x2 table). In this example I intend to find out do two groups differ in specific chemotherapies, Chemo 1 and Chemo 4 significantly differ, but what about Chemo 2?

Table looks like this:

Overall P <0.001

Variable / Group1 / Group2 / P value
Chemo 1 / 60 / 0 / <0.001
Chemo 2 / 40 / 1 / 0.011
Chemo 3 / 6 / 2 / 0.172
Chemo 4 / 1 / 8 / <0.001
]]>StatisticsMarkica85http://www.talkstats.com/showthread.php/70414-Appropriate-Bonferroni-correctionChoosing the right winsorizing method for outliers
http://www.talkstats.com/showthread.php/70411-Choosing-the-right-winsorizing-method-for-outliers?goto=newpost
Thu, 19 Oct 2017 12:31:23 GMTSo far, I've only been able to find references to 2 methods for winsorizing outliers: 1) substituting the outlier for the next higher or lower existing value in the dataset that is NOT an outlier, and 2) substituting the outlier for either the 5th or the 95th percentile ("90% winsorizing"). I wonder, though -- wouldn't it make more sense instead to set the outliers to the CUTOFF value that was used for identifying them in the first place? Would that not be a more conservative, and therefore reasonable, adjustment? Is that a known or accepted winsorizing method, and if not, why not?
]]>Statisticsogrfnklhttp://www.talkstats.com/showthread.php/70411-Choosing-the-right-winsorizing-method-for-outliers