What courses to take as an undergrad if I want to pursue a Master's/PhD?

[randomcat]

Hi, I'm currently a freshman at a large research university in California. My school offers 3 B.S. degree options: general statistics, applied statistics, and computational statistics. At first, I chose applied statistics because I hope to pursue a career in epidemiology or biostatistics in the future. After speaking to a graduate advisor, she tells me that it's OK if I don't have a lot of biology background when applying to a graduate biostatistics program. What's more important is my coursework in statistics. So she recommended me to work toward the general statistics option instead and tells me that the courses definitely prepare me better for grad school. My question is, what are some of the important curriculum that graduate admission officers look for? As you can see I do have some choices when it comes to choosing certain electives.
Thank you!

General Statistics Option:

Preparatory Subject Matter (30-32 units)

MAT 21A-B-C-D Calculus
MAT 22A or 67 Linear Algebra
MAT 25 Advanced Calculus
ECS 30 or 40 Intro to Programming/Software
Any one introductory statistics course except STA 10

Depth Subject Matter (51-52 units)

STA 106 Analysis of Variance
STA 108 Regression Analysis
STA 138 Analysis of Categorical Data
STA 131A-B-C Intro to Probability and Mathematical Statistics
MAT 125A Real Analysis
MAT 108 Abstract Math or 125B Real Analysis
MAT 167 Applied Linear Algebra

3 courses from:

STA 104 Nonparametric Statistics
STA 135 Multivariate Data Analysis
STA 137 Applied time Series Analysis
STA 141 Statistical Computing
STA 142 Reliability
STA 144 Sampling Theory of Surveys
STA 145 Bayesian Statistical Inference


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Applied statistics option:

Preparatory Subject Matter (26-31 units)

MAT 16A-B-C or 17A-B-C or 21A-B-C Calculus (21 series recommended)
MAT 22A Linear Algebra
ECS 30 Intro to Programming and Problem Solving or ECS 40 Intro to Software Development and Object-Oriented Programming
2 Introductory courses serving as the prerequisites to upper division courses in a chosen discipline to which statistics is applied
Any one introductory statistics course except STA 10

Depth Subject Matter (51-56 units)

STA 106 Analysis of Variance
STA 108 Regression Analysis
STA 138 Analysis of Categorical Data
STA 141 Statistical Computing
STA 130A-B Mathematical Statistics: Brief Courses

Three courses from:

STA 104 Nonparametric Statistics
STA 135 Multivariate Data Analysis
STA 137 Applied Time Series Analysis
STA 142 Reliability
STA 144 Sampling Theory of Surveys
STA 145 Bayesian Statistical Inference

Five upper division elective courses outside of statistics:

 

[Mean Joe]

My question is, what are some of the important curriculum that graduate admission officers look for?

Sorry, I don't know anything that can help you there.

I can comment on some of the courses that you mention:
The preparatory subject matter courses look good. While I can't imagine statistical work without software that already has the procedures (which use linear algebra, calculus, etc) ready to use, it's good to be able to write your own if necessary. eg in the future, we may develop new statistical methods. You can do a lot of statistics without knowing calculus/linear algebra, but you won't be able to make new statistics if you don't know it, imo.

The depth subject matter courses are good ones too. Take them as an undergrad, then take them again as a grad to really know what you're doing. As an undergrad you need to learn to be able to do, then as a graduate you need to learn to be able to teach ie you really need to know that stuff inside and out.

3 courses from:
STA 104 Nonparametric Statistics
STA 135 Multivariate Data Analysis
STA 137 Applied time Series Analysis
STA 141 Statistical Computing
STA 142 Reliability
STA 144 Sampling Theory of Surveys
STA 145 Bayesian Statistical Inference
I would suggest to really make an effort to take that applied time series analysis class. It's a really different kind of statistics, and a lot of data you will be seeing will come from subjects repeated at several time points.

 

[hlsmith]

You have some great options to select from. I may recommend at least taking Human Anatomy and Medical Techinical Terminolgy. You can fully function in the biostatistical world with limit medical knowledge, but it wouldn't hurt your application or general knowledge. Biostatisticians at times almost just function as data safety monitoring boards, I say this jokingly, since if you don't know the content you are already kind of blinded. It may also help to nail the quantitative part of your GREs, which with a stats background you would probably do regardless.

Lastly, I would also ask the chair or professor in the program you may be interested in. This not only will answer you question, but also get you on their radar.

 

[noetsi]

I think, as a practisioner rather than a researcher in stats, that it depends on what you want to do after you get out. The courses you described seem very good for academic research. In a practisioner environment you need to have information on how to present data (more likely to be taught I suspect in a business program than statistics), how to use SQL, and how to analyze financial data (probably from a finance program).

That assumes of course you are going to work in stats in a world where economics/financial analysis is most common - which I suspect the majority of the jobs doing statistical analysis are outside academics (which btw could be totally wrong). If you are going into biostatistics none of that may have any value. I would think a course in writing technical papers, and possibly one in SEM/factor analysis might be useful.

One thing to consider, the job you think you will do when you go to a university commonly is not the one you end up doing - if for no reason other than job markets change and there may be no openings. Lots of Phd's believe they will teach when they go into their program - then find out painfully there are a lot more job applicants for those than jobs.

 

[jackie2013]

Maybe get a double major.