Hi folks, I am currently working on a PhD in a social science program. Although the statistics training at my department is pretty good for a social science program, they emphasize the applied aspect (very much so) while I would like to have a more thorough theoretical foundation. In this regard, I have decided to take stat courses at the math/stat departments. Before I ask any question let me just give you some background information regarding my previous math/stat training:

#Undergraduate:

-Calculus (3 semesters)

-Linear Algebra

-Differential Equations

-Intro to Proofs

-Prob and Stats(non-calculus)

#Graduate(in my department):

*The following were done in a single semester long course:

-Basic Probability and Combinatorics

-RVs and Distributions (Normal, t, Binomial, Bernoulli but we did NOT cover: chi-square, poisson, geometric, neg-binomial, etc...)

-Statistics (CLT(did not prove), LoLN,Chebychev's Inequality, CI, Statistical Inference, OLS)

*next semester we will cover "problems" with OLS (heteroskedasticity, autocorrelation, etc), logit/probit regressions, and some of the RV distributions not covered in the first sem. And over the summer I plan to take two semesters of Real Analysis.

1) Given this, do I have to take the undergrad Probability(calc based) and Statistical Inference(calc based) at the math/stat department to take higher level stat courses?

2)Higher level stat coures I "plan" to take (rough list, please advice usefulness to social science research):

-Linear Regression Models

-Time Series Analysis

-Nonparametric Statistics

-Multilevel Models

-Causal Inference

I understand that grad level courses use measure theory (although i have no idea what that is) and my question is does undergrad Real Analysis 2 cover that? Here is a description of the course:

"Equicontinuity. Contraction maps with applications to existence theorems in analysis. Lebesgue measure and integral. Fourier series and Fourier transform"

Are any of those courses not advised for a social scientist? Would you add any other courses to the list?

EDIT: Also let me add that I am not too bad at math, although nowhere close to stellar. (For what its worth GRE-Q was 780)

#Undergraduate:

-Calculus (3 semesters)

-Linear Algebra

-Differential Equations

-Intro to Proofs

-Prob and Stats(non-calculus)

#Graduate(in my department):

*The following were done in a single semester long course:

-Basic Probability and Combinatorics

-RVs and Distributions (Normal, t, Binomial, Bernoulli but we did NOT cover: chi-square, poisson, geometric, neg-binomial, etc...)

-Statistics (CLT(did not prove), LoLN,Chebychev's Inequality, CI, Statistical Inference, OLS)

*next semester we will cover "problems" with OLS (heteroskedasticity, autocorrelation, etc), logit/probit regressions, and some of the RV distributions not covered in the first sem. And over the summer I plan to take two semesters of Real Analysis.

1) Given this, do I have to take the undergrad Probability(calc based) and Statistical Inference(calc based) at the math/stat department to take higher level stat courses?

2)Higher level stat coures I "plan" to take (rough list, please advice usefulness to social science research):

-Linear Regression Models

-Time Series Analysis

-Nonparametric Statistics

-Multilevel Models

-Causal Inference

I understand that grad level courses use measure theory (although i have no idea what that is) and my question is does undergrad Real Analysis 2 cover that? Here is a description of the course:

"Equicontinuity. Contraction maps with applications to existence theorems in analysis. Lebesgue measure and integral. Fourier series and Fourier transform"

Are any of those courses not advised for a social scientist? Would you add any other courses to the list?

EDIT: Also let me add that I am not too bad at math, although nowhere close to stellar. (For what its worth GRE-Q was 780)

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