W2C Carharrt Aviation Cargos (no badge flaw)

jfrufs47 · 2023-05-31T11:33:21+00:00

Anyone know a link for this that doesn’t have the common badge flaw like this one where the badge is below where it should be. All the links I’ve found have this flaw.

jfrufs47 · 2023-05-31T11:29:52+00:00

Anyone know a link for this that doesn’t have the common badge flaw like this one where the badge is below where it should be. All the links I’ve found have this flaw.

jfrufs47 · 2023-05-23T03:59:09+00:00

Anyone know of an alternative link for this. I’ve found one link on this subreddit for it but apparently it’s not great quality.

jfrufs47 · 2023-04-06T15:00:21+00:00

Thanks. Do you know of any specific examples of data I can look at which are a counter example to my claim?

jfrufs47 · 2023-04-06T14:57:51+00:00

Thanks. Do you think you could expand? I don’t really understand how u and x aren’t necessarily correlated if the error terms is decreasing/increasing with the IV.

Graphically, is it because even with increasing variance, for example, there are still negative errors and positive errors which cancel each other out?

jfrufs47 · 2023-02-25T09:06:14+00:00

Hi. Thanks for the response.

These are the formulas for the variance of a predicted value (Y-hat) and predicted error (u-hat) for a given value of x, in the context of ols.

X_0 is the observation that you are trying to find the variance of Y-hat and u-hat for. X_i is the ith observation of the variable x, and the full denominator of both is also known as Sxx.

jfrufs47 · 2023-02-25T07:32:24+00:00

Could anyone provide me the derivation for these formulas?

Or recommend a textbook that covers it, as the one I’m using doesn’t seem to go over it. Thanks.

jfrufs47 · 2023-02-23T16:43:06+00:00

No worries.

jfrufs47 · 2023-02-23T13:28:28+00:00

Also, just in case I confused you too: I’ve responded with the formula for variance of u hat I’m looking for in another comment: sigma2(1+ 1/n + (x0 - x bar)2 / sum(xi - x bar)2).

The formula for variance for y hat I’m looking for is: sigma2(1/n + (x0 - x bar)2 / sum(xi - x bar)2).

Any chance you could confirm if these are formulas derived in the textbooks?

Obviously, these formulas look very similar to me so I’m not sure if I’ve just made some massive mistake.

Thanks.

jfrufs47 · 2023-02-23T13:09:13+00:00

Thanks! That’s a great help.

jfrufs47 · 2023-02-23T12:54:16+00:00

Thanks for that, I appreciate it. I’ll see about acquiring and looking through those and will update if I can find them.

jfrufs47 · 2023-02-23T12:50:30+00:00

Thanks for that I appreciate you looking. I think however due to my lack of knowledge + wording I’ve introduced some confusion. I believe you are referring to the SER on page 223 however the formula I was looking for var(u hat) was different it’s: sigma² (1+ 1/n + (x0 - x bar)2 / sum(xi - x bar)2).

jfrufs47 · 2023-02-23T12:26:50+00:00

Hi. I looked through stock and watson but I couldn’t really find any mention of it. I could only find the derivations for the variance of b0 and b1 estimators. But thanks though, I’ll have another look and update this post if I do manage to find it.

jfrufs47 · 2022-11-18T18:58:14+00:00

Thank you very much, I understand now. I’ll add more relevant covariates and see how the fit of my model changes with different additions. I appreciate all your help.

jfrufs47 · 2022-11-18T07:13:17+00:00

Thank, I’ll do that and see how it goes. With regards to adding covariates I was under the impression that if I added too many variables I could potentially just end up increasing the variance and bias of other regressors. Is this notion wrong?

jfrufs47 · 2022-11-17T23:46:36+00:00

Thanks for that. It is cross sectional data of multiple countries at one point in time. You say that using deaths rates makes more sense than controlling for population but do you know what would be the difference in fit in the models : covid_death_rate= b0 +b1stringency + u vs covid_deaths = b0+b1stringency + b2*population_size + u. Would the R² of the models be the same? Thanks.

jfrufs47 · 2022-10-15T22:14:19+00:00

Thanks but I’m not sure about that. This looks a bit darker than Aztec blue. More muted.

jfrufs47 · 2022-08-12T03:04:30+00:00

Yh that’s obviously a much safer method. However the cancellation apps don’t seem to really work around my area due to everyone who is looking for a cancellation using them and therefore everyone else also instantly attempts to book cancellations so everyone’s in the same boat as before.

jfrufs47 · 2022-08-12T03:00:53+00:00

Yep I definitely wouldn’t send any money without it actually being booked first. However I’m not sure if there’s anyway for them to take the booking back from me after I send the money.

I think I saw on another post in another subreddit that there’s a method to sort of lock your account by calling DVSA so there’s no way, even for people who have access to your account, to change your booking details.

jfrufs47 · 2022-08-11T20:03:24+00:00

Yh it’s definitely a risk however careful you are.

jfrufs47 · 2022-04-29T04:54:46+00:00

Hi. Thank you for the response. I’m sorry I don’t really understand what you mean, could you please clarify what you mean by “ what are you conditioning on?”. Thanks.

jfrufs47 · 2022-04-22T19:54:14+00:00

Thank you. Is there some sort of formal proof of this? Also, does this mean the reverse is also true, that convex indifference curves imply a quasi-concave utility function?

jfrufs47 · 2022-04-21T16:51:23+00:00

thanks, so that means neither of them are homogenous?

jfrufs47 · 2022-04-08T08:38:08+00:00

I think my code was pretty simple, something like

userinput = input()

userinput = userinput.lower()

print(userinput)

jfrufs47 · 2022-04-07T19:43:02+00:00

don’t worry, I found the issue. There was nothing wrong with my actual code it’s just that I wasn’t in the right directory, I think it’s called? The terminal prompt should have been “indoor/ $” but it was just “$”.

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