ANOVA requires independence of observations, meaning that the data points should not be influenced by each other. Violations of this assumption, such as in clustered or correlated data, can affect the validity of ANOVA results. Analysis of Variance assumes homogeneity of variances, meaning that the...
1. At the beginning I though that you would fit the final model only once with the entire dataset but here you are referring to “each time” meaning that you are fitting it several times, and if it is the case with what? Always with the entire dataset? Or parts of it? 2. The ...
For instance, in our example −Data set 2 has a standard deviation of 1.41, meaning the numbers in that set are typically within 1.41 units of the mean (which was 10). Data set 1, however, has a standard deviation of 14.14, meaning its numbers are usually much farther from the mean...
Your current environment The output of `python collect_env.py` Your output of `python collect_env.py` here 🐛 Describe the bug For vllm online mode, I observed the logprob is slightly different with same prompt, same openai client paramet...
The target function is estimated from the training data by a machine learning algorithm, so we should expect the algorithm to have some variance. Ideally, it should not change too much from one training dataset to the next, meaning that the algorithm is good at picking out the hidden ...
sources of variation in the data by breaking it down into between-group and within-group variance, thus enabling researchers to understand how much variability can be attributed to group differences versus randomness. Moreover, ANOVA has high statistical power, meaning it is efficient for detecting ...