Designing comparative experiments

Designing comparative experimentsKrzywinski, M., Altman, N., 2014. Points of significance: Designing comparative experiments. Nat Meth 11, 597598. doi:10.1038/nmeth.2974

(a) Two treated samples (A and B) withn= 17 are compared to a control (C) withn= 17 and to each other using two-samplet-tests. (b) Simulated means andPvalues for samples ina. Values are drawn from normal populations with= 1 and mean response of 10 (C), 10.6 (A) and 11 (B). (c) The preferred reporting method of results shown inb, illustrating difference in means with CIs,Pvalues and effect size,d. All error bars show 95% CI.Krzywinski, M., Altman, N., 2014. Nat Meth 11, 597598.

(a) Limits of measurement and technical precision contribute towit(gray circle) observed when the same aliquot is measured more than once. This variability is assumed to be the same in the untreated and treated condition, with effectdon aliquotxandy. (b) Biological variation gives rise tobet(green circle). (c) Paired design uses the same aliquot for both measurements, mitigating between-subject variation.

(a) The samen= 17 sample is used to measure the difference between treatment and background (A = Aafter Abefore, B = Bafter Bbefore), analyzed with the pairedt-test. Two-samplet-test is used to compare the difference between responses (B versus A). (b) Simulated sample means andPvalues for measurements and comparisons ina. (c) Mean difference, CIs andPvalues for two variance scenarios,bet2/wit2of 1 and 4, corresponding toof 0.5 and 0.8. Total variance was fixed:bet2+wit2= 1. All error bars show 95% CI.

http://www.stat.ubc.ca/~rollin/stats/ssize/n2.html

http://in-silico.net/tools/statistics/ttest

https://www.mccallum-layton.co.uk/tools/statistic-calculators/confidence-interval-for-mean-calculator/#confidence-interval-for-mean-calculator

A/C