Recommended courses for Graduate school

I am trying to prepare for a PhD in Statistics and am looking for advice on how to prepare/gain admission to a good program.

I am looking at completing an undergrad in math and earning a masters in applied statistics (Already have an undergrad in Econ) or just completing a masters in applied math. Which of the two options would be more helpful in preparing for a PhD and in gaining admittance?

As well how much computer science/programming should one know? Do I need a minor in CS or the equivalent knowledge of, or just the basic intro to programming courses.

I had thought that doing completing the equivalent of a minor in CS would be necessary and I would be better off with the Masters in Applied Math while taking a Numerical Linear Algebra, Real Analysis 1 & 2, Math Stats 1 & 2, Stochastic processes 1 & 2, Optimization 1 & 2, and maybe the sequence of Numerical Analysis and/or Complex Analysis.

If anyone has any opinions or advice that would be great! I had wondered if Abstract Algebra of Topology courses would be helpful as well, there is a sequence of both offered in the Applied Math program I'd be in. I will have completed Cal I-III, Linear Algebra, Diff Eq, a probability course that does not require RA, and Discrete Math prior to the Master's. If I continue to do the undergrad only many of those courses are dual listed and I could complete them as an undergrad.

Any suggestions/advice outside of this is welcomed as well. Thanks in advance if anyone takes time out of their busy schedule to reply!

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You should know how to program. That's not the same thing as knowing the syntax of a particular language. What it does mean is that, if there is a real problem that you need to solve, you can use the computer on your own to solve it. You can take classes, but that's enough. If you enjoy programming, you will learn how to program. If you don't, you won't...

Learn Matlab / Octave.

Take classes on Bayesian statistics if they are offered. It pays to go Bayes...
Thanks Jessica! Here is a more complete description of what I am trying to do...figure out my plan from here to application. I posted this over at the grad cafe so sorry if any of you are reading it in two spots.

I am planning out my next two years of Math/Stats course work before applying to a Statistics PhD program. My background....I have done two undergrad degree's the first one was miserable and was years ago...I assume most adcom's will look past that.

By the end of this summer I will have completed:
Intro Linear Algebra
Probability Theory
Applied Differential Equations I
Programming I (Python)
Econometrics **(Don't know that this is relevant)
Econ Forecasting **(Don't know that this is relevant)

Here is what I am looking take/do (the courses in italics I figured were what I should take:
This is for the coming summer, undecided here but believe the intro to scientific computing is more relevant:
Intro to Scientific computing (believe this is Mathematica based course based on numerical analysis) or Programming II (Python)

Fall 2011
Intro to Real Analysis I

Unsure what to take in the fall semester here are the options:
Math Stats w/applications I **(More rigorous option in Masters program but this is required for stochastic processes in the spring, I don't know if taken math stats twice is good or bad??)
Numerical Analysis I
Linear Optimization Theory (linear programming)
Applied Differential Equations II (recommend by grad advisor for applied math degree, but maybe not applicable for Stats PhD?)
Foundations of Computer Science
Programming III C++ (If I took Programming II in the summer)

Spring 2012/Summer 2012
Advanced Linear Algebra
Intro to Real Analysis II
Advanced Calculus
Principles of Modern Algebra I (recommended by grad advisor)
Stochastic Processes w/Applications I
Math Stats w/Applications II
Data Structures and Algorithms for CS

**Are four math courses a recipe for disaster? As well I have conflicting advice from advisors, professors, and PhD students on the Modern Algebra. It seems adcoms want heavier math but the math is rarely I mentioned I have a strike against me due to my first poor showing in undergrad years ago.

Fall 2012-Summer 2013 (MA in Applied Math)
Real Analysis I & 2 (definitely taking)
Numerical Linear Algebra
Intro to Complex Calculus (this can be taken as an undergrad too, one of two courses offered in summer; only can take it as an undergrad if people think it is advisable to take 4 courses in one of the semesters)
Stochastic Processes w/Applications II (only if I could handle 4 courses in a semester)
Graph Theory with Applications (It's one of two courses offered in the summer, gets me out in a year)

I am required to take two of these sequences:
Math Stats I (more advanced than the undergrad version) (undergrad or grad?)
Numerical Analysis I & 2
Linear Optimization I & Non Linear Optimization Theory I

Is it feasible/logical to take four math courses a semester in grad school? I assume one could do it and get the grades....but I want to learn the material. If not that rules out Stochastic applications, and Numerical Linear Algebra or RA 2.

Opinions, advice, thoughts, are all appreciated! Thanks for taking the time to look at my post. As well I could do a MS in stats instead of Math, but I assumed Math Stats I & II, Numerical LA, RA 1 & 2, and stochastic processes were almost two thirds of the degree and would help strengthen my application. I am trying to apply to a more theory oriented program and the Master's here would be applied and less math intensive i.e. no RA required. I have been advised by various adcom's to take math and I will learn stats when I get there...other PhD's have advised the opposite...learn linear algebra, RA, and stats.

Thanks in advance, I know it is a lot but I have spent considerable time trying to come up with some sort of optimal solution to get in a good program. I currently have a math GPA of 3.75, with one B. If successful and assuming I can maintain a 3.75 or better and achieve a 3.5 or better in grad school what tier programs could I look at applying to. I assume I can bring the math GPA up as it had been some years since my last math course (10ish years). I am set on nothing and would scrap and start over...just trying to give my best shot at getting in a good program.

Thanks again for taking the time out of your busy schedule to read this!

Can someone give a clear distinction on the value of an applied stats phd vs a more traditional route and the advantages/disadvantages if someone was likely to go into industry?