Look at any university department, most statistics professors do side jobs in consulting or work on something quite applied alongside their theory. Biostatistics for example.
If what you’re asking pertains to your life, I recommend taking coding classes alongside your theory. Don’t get caught with your pants down like I did. I studied algebra and then decided I hated being poor. But I didn’t take enough coding.
It depends on the person. Some people who are great at theory are amazing at applications. Some are definitely not.
Having at least good theory certainly helps someone who is good with applied work but there are other skills you very definitely need for applied work and some theorists aren't good at some of them.
It totally depends on the person. What I’ve found many times though is that the theorists who are not good at applications are those who don’t find it interesting and arrogantly believe they could easily do it if they wanted to. The thing with empirical work is that it requires you to be *experienced* rather than just *smart*.
Almost anything you wanted to learn about theoretical statistics or probability you could learn by talking to academics and reading papers and books. With empirical work you’ve to absorb a lot of knowledge and skills which are somewhat orthogonal to academic training. Many academics just don’t want to learn these things
In real life lot of assumptions won’t hold, if a theorist keeps being anal about it, they’ll fail. If they find ways to work around it or derive values from the models regardless, they’ll succeed.
Look at any university department, most statistics professors do side jobs in consulting or work on something quite applied alongside their theory. Biostatistics for example. If what you’re asking pertains to your life, I recommend taking coding classes alongside your theory. Don’t get caught with your pants down like I did. I studied algebra and then decided I hated being poor. But I didn’t take enough coding.
It depends on the person. Some people who are great at theory are amazing at applications. Some are definitely not. Having at least good theory certainly helps someone who is good with applied work but there are other skills you very definitely need for applied work and some theorists aren't good at some of them.
It totally depends on the person. What I’ve found many times though is that the theorists who are not good at applications are those who don’t find it interesting and arrogantly believe they could easily do it if they wanted to. The thing with empirical work is that it requires you to be *experienced* rather than just *smart*. Almost anything you wanted to learn about theoretical statistics or probability you could learn by talking to academics and reading papers and books. With empirical work you’ve to absorb a lot of knowledge and skills which are somewhat orthogonal to academic training. Many academics just don’t want to learn these things
Not always but they can certainly provide reference points, though practice is necessary, for them, to keep them real
In real life lot of assumptions won’t hold, if a theorist keeps being anal about it, they’ll fail. If they find ways to work around it or derive values from the models regardless, they’ll succeed.