2 votes

How can I back transform a log data to interpret t-test and get original CI?

I can log-transform it to be normally distributed, and then perform a t-test and get confidence intervals (CI). But how do I interpret the results of the t-test and the CIs? If you want to compare 2 ...
  • 68.8k
2 votes
Accepted

Logistic regression: What are use cases for logistic regressions where $n \neq 1$, i.e., $n >1$?

Assuming that your $n$ is the number of cases of each type, you end up looking at proportions of each successful rather than $0-1$ and you weight by $n$. Stealing from https://stackoverflow.com/...
  • 32.4k
2 votes

Prove E[Y|X] = f(X)

$\mathbb{E}[Y|X] = \mathbb{E}[f(X)+\epsilon|X] = \mathbb{E}[f(X)|X]+\mathbb{E}[\epsilon|X] = \mathbb{E}[f(X)|X]+\mathbb{E}[\epsilon] = f(X)+0$
  • 2,301
1 vote

Modelling losses in insurance - why nobody seems to talk about left-truncated distribution?

Even if the gof is amazing, is it not theoritically "wrong" to use non-left-truncated distributions for this kind of things? If it is the case that some simple parametric distribution fits ...
1 vote

Modelling losses in insurance - why nobody seems to talk about left-truncated distribution?

I assume that retention left-truncates the severity distribution and deductible does so for both the frequency and severity distributions (even in a less predictable way that the former). If an ...
  • 662
1 vote

Is this a known measure of "effective degrees of freedom" in regression?

This quantity seems to reduce to "Welch-Satterthwaite degrees of freedom" is the limit of variance of $x,y$ going to 0
1 vote

How to show for positive Borel functions $g, \int_{a}^{b} g(x)dF(x) = \int_{a}^{b} g(x)f(x)dx$

Albeit the concerns re the ambiguities as shown in the comments deserve clarification, these sort of problems are standard measure theoretic exercises. So, I am leaving below a general brief ...

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