Getting a graduate degree in Statistics. Everyone who hears offers me help because they already took statistics...

That's not bad advice. Very few people I know had any idea what Bayesian Statistics was when I took a class on it, let alone Mixed Effects Modeling.

I got an A in Intro Stats, so if you need any help, feel free to ask.

I feel you. Everyone thinks a driver’s license is a license to practice transportation engineering...

I never had that problem. I have a graduate degree in computer engineering and a friend of mine has a graduate degree in chemical engineering. When we were in school and people heard what we were study, they’d say, “wow, you must be smart.”

That being said, if you need any help with R, just post here.

I'm in a similar boat: finishing a masters degree in math, writing my thesis on a topic in nonparametric statistics.

I've never experienced this. Strange people you find.

I bet you are good at playing the lottery.

37% of statistics are made up, so you can cruise this and come off real important, lying while waving this degree and getting people to believe you.

That is silly that neophytes offer you help in stats! Having said that, I'm an engineer that deals with physics based models and I sometimes have to deal with statisticians over-interpreting cause-effect things that have nothing to do with the underlying physics. I think statisticians are brilliant, especially PhD level ones, but please don't forget that trying to model a dynamic system, where the physics is known well by using a Design of Experiments polynimial curve-fit response surface function, is going backwards (not as good). Then there are Nueral Net models that can pick up on unmodeled physics that can bring out phenomenon that you miss with physics based modeling. There are pros/cons with each. Physics based models require much less data to identify model paramaters (each time point in the experiment is a data point) and the model paramaters have physical meaning. Input/Output models (NN and the polynomial models) require a lot of data to id or train models (each exeriment is only one data point at the end of the experiment) and the model paramaters don't have any physical meaning. When you don't know the physics, the DOE approach is great for screening variables and is very simple to use. They all have their place and a modeler should be familiar with each kind and when each should be used. I see a lot of stats folks stuck, even at the PhD level, only using some of these tools.

Cool story but no need to get all butthurt about it

It is just part of a larger trend where anyone with access to google is an expert on everything. Look at all the virologists and Russian military experts on this board.

The world around us keeps getting more complex over time but biologically we haven't changed at all since pre-civilization. People are mostly lost in this sea of stimulation and complexity, and the tendency is to go with your gut instincts and try to make sense of it all using a primitive thought process. The worst part is that everyone wants to be heard and for their opinion to count so they give their 2 cents on just about anything they have no clue about. Even worse is the growing number of people who do this with very high conviction. To summarize, the more educated you become and the more sophisticated your thought process, the more you contrast with the mouth breathing ignorant masses around you. It is an easy explanation, and no surprise someone like Trump can become president. While true that the more you learn the less you realize you know, but we are all better off with well educated people having high-conviction views because if they don't the dumb@sses of the world will continue to have more influence.

Well, I mean, I do hear you, but, perhaps you fellows ought to at times ask users of a given road or intersection for some feedback before you deploy some of your great ideas...just an fyi.

A strong dose of the nuances of physical models of dynamical systems contrasted against the explanatory limitations of neural net driven machine learning approaches is just what LR folks needed.

Yes, everyone that offered help to you is dimwitted. It would be like a pregnant mother of 4 receiving an birthing offer of help from a bachelor who saw his chihuahua give birth to puppies.

You think that's bad? Try being a psychologist.

"My cousin ..... what do you think is wrong with them"

"I was a minor in psychology"

"What a fascinating field, I want to be a profiler"

"Last night I watched a thing on serial killers and ..."

"My therapist told me ...."

"You're going to psychoanalyze me better not talk to you" (people who say this also have an odd compulsion to then continue talking to me)

It’s fine to have opinions, but recognize that if you disagree it’s probably either because (a) you’re misinformed (b) you and the engineers have different goals or (c) the engineers are dealing with constraints of which you’re blissfully unaware, not that they’re idiots.

People think they’re so funny when they say “I bet you could diagnose me with something.”

Isn't it innate human behavior to try to find a connection with someone else?

It's not that everyone is dumb, it's just that people are searching for common ground.

In other words, lighten up!

So statistically not distinguishable from everything else in the UK, like the pound for example?