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Inferential statistics cannot separate variability due to treatment from variability due to experimental units when there is only one measurement per unit. Sacrificial pseudoreplication (Figure 5b in Hurlbert 1984) occurs when means within a treatment are used in an analysis, and these means are tested over the within unit variance.
Replication in statistics evaluates the consistency of experiment results across different trials to ensure external validity, while repetition measures precision and internal consistency within the same or similar experiments. [5] Replicates Example: Testing a new drug's effect on blood pressure in separate groups on different days.
Classic data sets; Classical definition of probability; Classical test theory – psychometrics; ... Pseudoreplication; PSPP (free software) Psychological statistics;
Also confidence coefficient. A number indicating the probability that the confidence interval (range) captures the true population mean. For example, a confidence interval with a 95% confidence level has a 95% chance of capturing the population mean. Technically, this means that, if the experiment were repeated many times, 95% of the CIs computed at this level would contain the true population ...
Ignoring these dependencies, the analysis can lead to an inflated sample size or pseudoreplication. While a unit is often the lowest level at which observations are made, in some cases, a unit can be further decomposed as a statistical assembly. Many statistical analyses use quantitative data that have units of measurement. This is a distinct ...
Let a be the value of our statistic as calculated from the full sample; let a i (i = 1,...,n) be the corresponding statistics calculated for the half-samples. (n is the number of half-samples.) Then our estimate for the sampling variance of the statistic is the average of (a i − a) 2. This is (at least in the ideal case) an unbiased estimate ...
Pseudoreplication is defined as the use of inferential statistics to test for treatment effects with data from experiments where either treatments are not replicated (though samples may be) or replicates are not statistically independent.
Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. [1]