Top new questions this week:
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I’ve encountered an interesting discussion at work on interpretation of precision (confusion matrix) within a machine learning model. The interpretation of precision is where there is a difference of …
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Why do we need normality test if the sample size is large enough and hence, the distribution of the sample mean is approximately normal based on central limit theorem?
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I have taken hourly-based wind power data, by taking its periodogram after making it stationary in R. It gives me four seasonal patterns at periods of 24, 12, 08, and 06, as shown in the figure below. …
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A proportional hazards model $\lambda_i(t|x_i) = \lambda_0(t)\exp\{x_i^T \beta\}$ can be approximated using a piece-wise constant hazard, where the duration is partitioned into intervals and the …
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I am reading this article about the horseshoe prior and how it is better than lasso and ridge priors. The author makes several points that I don’t understand. One of them is “The ideal prior …
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I have been pretty confused about maximum likelihood as expressed by my question here. But this question is not about MLE. It occurs to me my confusion may have been because the likelihood function …
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I was comparing results that I generated in R for complex survey analysis using the survey package to results from SPSS using the complex samples analysis add-on. The sample size is large ~ N=5500 …
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Greatest hits from previous weeks:
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I am lost in normalizing, could anyone guide me please. I have a minimum and maximum values, say -23.89 and 7.54990767, respectively. If I get a value of 5.6878 how can I scale this value on a scale …
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I was asked today in class why you divide the sum of square error by $n-1$ instead of with $n$, when calculating the standard deviation. I said I am not going to answer it in class (since I didn’t …
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I am reading a data mining book and it mentioned the Kappa statistic as a means for evaluating the prediction performance of classifiers. However, I just can’t understand this. I also checked …
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In the context of neural networks, what is the difference between the learning rate and weight decay?
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I recently used bootstrapping to estimate confidence intervals for a project. Someone who doesn’t know much about statistics recently asked me to explain why bootstrapping works, i.e., why is it that …
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When running a multiple regression model in R, one of the outputs is a residual standard error of 0.0589 on 95,161 degrees of freedom. I know that the 95,161 degrees of freedom is given by the …
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Maybe the concept, why it’s used, and an example.
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Can you answer these questions?
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Good evening everyone, I am here to ask a question regarding the statistical models ARIMA & SARIMA use to build predictive models based on past values and with the intent of predicting future …
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Given two probability densities $p(x)$ and $p(y)$, define the dot-product of their log-likelihood gradients, also sometimes known as “scores”, $\langle \nabla_x \log p(x), \nabla_y \log p(y) …
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In my stats class, we are talking about the 2 proportion $Z$-test, which compares two sample proportions. The test statistic is given as: $$ Z = \frac{\hat{p_1}-\hat{p_2}}{\sqrt{\hat{p_c}(1-\hat{p_c})…
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