I'm am a control engineer and I want to upgrade my skills in simulation of dynamic physical systems. Normaly I describe my physical system as transferfunction or a statespace model depending what I want to know.

But those models are not exactly equal to the system. Very old technique. So I want to learn ARX, ARMAX, Box-Jenkins and Output-Error modeling to create a better dynamic model for simulation. Modern technique.

The problem is that I don't know anything about statiatics, probability, Inference and regission.

But I have downloaded 13 playlist from JBstatistics at youtube. I'm planning to watch them depending what I need to know.

The names of those playlists are:

- Discrete probability distribution

- Continuous probability distribution

- Hypothesis testing

- Inference for variances

- One-way ANOVA

- Inference for proportions

- Inference for population means

- Confidence intervals for population means

- Simple linear Regission

- Chi-Square test for Count data

- Using a standard Normal table

- Sampling distribution

Questions:

1. Do I really need to know all those to learn more about statistical regissions analysis? Or could I only jump directly to regissions analysis? I don't want to waste any time on statistical methods that I not going to use in control engineering.

2. Am I right that to create ARX, ARMAX, BJ and OE models, I need to know regissions analysis, not statistical inference/distribution?

3. If i need to know all those, can you say in what order I should watch them?

Ofc I know the programming language R.