Hey /sci/, undergrad CompSci major. I've been interested in DSP and signal processing (keep in mind I have no real experience with either, the IDEA seems fascinating), and the CompSci degree track allows me to take "concentration electives" in any related discipline I seek to study.

My question is, if I were to take, say
>Signals and Systems
>DSP
>Random Signals and Noise
>Communications Systems Engineering ~or~ Digital Audio and Image Signal Processing

Would I have a sufficient education in the field? Do engineering firms hire people who are "DSP" guys specifically, or are they looking for straight up Electrical/computer Engineers? Note: I can take those classes above and still take a large amount of Software Engineering classes at the same time. Will any of this cross-over to the private sector, or will my DSP training just not be sufficient to work with it?

I'm having trouble sifting through metric tons of data all stating different things about climate change. To me it seems that a lot of sources seem to either be unsupported by reliable studies and evidence, or have a very intentional bias which distorts actual evidence. Can anyone give me some help on this?

will human evolve in the future ?

What does /sci/ think about Bayesianism?

Do you ever use Bayesian approaches?

Guys please help me out. What is the charge(in Coulomb) of Argon2plus and how can one know charges of molecules?

I have the following stats electives to choose from. Which seems the most interesting to you?

- Applied Nonparametric Statistics: Methods of analyzing data from non-normal populations including binomial tests, contingency tables, use of ranks, Kolmogorov-Smirnov type statistics and selected topics.

- Statistical Decision Theory: Development and use of probability and statistics for strategic decision making with applications. Topics include decision flow diagrams, analysis of risk and risk aversion, utility theory, Bayesian statistical methods, the economics of sampling, sensitivity analysis and collective decision making.

- Probability and Mathematical Statistics II: Topics include estimation via MLE and the method of moments, interval estimation, minimum variance estimators, Bayesian estimation, hypothesis testing, inferences based on normal distribution, two sample inferences, goodness-of-fit tests.

Hello /sci/

In the event of a apocolyptic disaster that cripples modern society, what STEM degrees would be the most useful to your survival and the rebuilding of your community? Not mad max tier post apoc, but something along the lines of The Last of Us.

Is there any way to find out about recent satelites breaking up in the atmosphere?

Today (17:47, Erlangen, Germany) I saw something bright wiz across the sky and the visibly split into brighter pieces before disappearing. The weird thing is that the the sky seemed overcast (it was dark so I wasn't sure, but there were no stars). Is there any way I could find out what it was? I don't suppose some agency tracks shooting stars and the like, but I might have more luck with satelites.

ENGLISHMEN ARE THE ABSOLUTE MASTERRACE OF ALL SCIENCES

PROOF OF MASTERRACE STATUT (compared to frenchies)

English Dominion forces:
> Newton
> Dirac
> Dyson
> Fisher
> Gowers
Etc

Frenchie Peasant forces:
> Descartes (kek)
> Pascal
???


Another little known fact is that frenchies actually don't even know the difference between "repulsion" and "attraction." It just escapes their mind.

Multiple regression, I need assistance. I only know a bit of bivariat regresion.

Three successive multiple regression models predicting the amount of sexual partners.

Dependent variabel= number of sex partners (the total amount of sex partners)

Variables:
Female (Men=0, Female = 1)
Age (age in in years)
Educ_years (education in years)
Sex_debut (age of respondents sexual debute)

Question 1)
What's the predicted amount of sexpartners for a 30 year old female according to model 1?

Question 2)
What happened with the variable Age in model 3?

Question 3) What's the predicted amount of sex partners for a 30 year old women according to model 3?

Question 4) What variable has the strongest effect on the amount of sex partners according to model 2?

Question 5)
How does one interpret the regression coefficients of the variables Age_x_age and sex_debut in model 3?


If you help me I'll share my porn; I have some rare stuff indeed. If porn is not in your taste then we can probably arrange something else.