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The Assumptions of ANOVA - ROHAN Academic Computing
The Assumptions of ANOVA - ROHAN Academic Computing

Tests for Serial Correlation in Mean and Variance of Time Series
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... The estimated difference of 5.12 is not statistically significant at the 5% level; t = 1.7, p = 0.9. Explain the make up of the Pooled Standard Deviation. The sum of squared deviations from the mean is calculated for each sample separately and then pooled, that is, added, and the average squared dev ...
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... We assume here that the population may be modelled using a normal distribution with unknown mean  but known variance 2 For example, suppose one wants to investigate IQ of students at StAndrews. As you cannot study the whole population, you need to measure the IQ’s of a random sample of students. I ...
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... 15. a. H0: μ < 50 (endurance is not increased). The critical region consists of z-scores beyond z = +1.65. For these data, σM = 1.70 and z = 1.76. Reject H0 and conclude that endurance scores are significantly higher with the sports drink. b. H0: μ = 50 (no change in endurance). The critical region ...
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... were asked to give themselves and each other a grade on their contribution to the group. A random sample from two of the teams yielded the following results: Q R X Q = 87.5 ...
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Resampling (statistics)

In statistics, resampling is any of a variety of methods for doing one of the following: Estimating the precision of sample statistics (medians, variances, percentiles) by using subsets of available data (jackknifing) or drawing randomly with replacement from a set of data points (bootstrapping) Exchanging labels on data points when performing significance tests (permutation tests, also called exact tests, randomization tests, or re-randomization tests) Validating models by using random subsets (bootstrapping, cross validation)Common resampling techniques include bootstrapping, jackknifing and permutation tests.
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