<p>I am a recent graduate student from UCLA and planning to obtain my master degree in statistics due to the current economics crisis that cause me couldn't find a job. I am holding an economics major with a statistics minor from UCLA, My overall GPA is 3.4 and statistics minor GPA is 3.7. I am considering the Cal State East Bay Master of Statistics program, but I was told by a recruiter that the master program in Cal State is essentially helpless in terms of job prospect because company only care about the reputation of that particular university. That recruiter suggested me to consider a more prestigious University such as UC Berkeley and UC Davis. How do the UCB and UCD master of statistics program compare to the East Bay Cal State statistics program?</p>
<p>Companies don’t “only care about the reputation,” but it is true that you’d be better-served by a degree from Cal or UC Davis.</p>
<p>While these three universities are all in the same state, their stat departments are not even in the same universe! </p>
<p>Go to Berkeley or Davis if you can.</p>
<p>However, a professor from Cal State East Bay had told me he graduated with MS in Stats from UCD but barely know anything about data analysis. Not to mention that the tuition is relatively expensive in UC.</p>
<p>And he is teaching in Cal State Esat Bay? I do not know what to say.</p>
<p>Berkeley’s stat program is far superior than a Cal State (as a UCLA grad, I’m shocked that you even have to ask the question), but also a lot more competitive. Also be aware that Cal requires that you already completed upper division math courses.</p>
<p>The reputation of your program matters, but it really depends on what you want to do. If you want to work at a top company or medical research center, then the degree matters more than if you just want a job doing anything. There are so many jobs for statisticians out there right now that I would say that even though your graduate degree matters, I would get an MS at Cal State before I got no MS at all or if I could not afford Berkeley or Davis.</p>
<p>Apply to all three, and make your decision in April once you have your results. Most likely you will have to pay for an MS in statistics out of pocket or with loans, but most MS program in stats that I have seen are only one year full-time as long as you have the math prerequisites. Since you were an economics major and a stats minor, I’m assuming that you already have calculus and linear algebra out of the way.</p>
<p>@juillet
I took 6 upper division stats classes at UCLA but I DID NOT take any linear algebra course. I KNOW, I suffered from my linear model class but I eventually got an A by studying linear algebra material by myself. I am afraid I could not complete the classes in one year if I would choose to go to UC and the master of stats program in Cal State is a two years program. </p>
<p>@bluebayou
I know the different between the state university and the UCs. However, I do not see any difference in terms of job prospect. couple friends of mine graduated from San Jose State but land a job in morgan stanley and the friend who graduated with me from UCLA working in a small insurance company. I just want to know the difference between the three programs in terms of job prospect in a future career.</p>
<p>San Jose State is sort of a special case. Because of its location in Silicon Valley and close ties to industry there SJSU graduates are highly regarded by many employers and often will be chosen over most UC graduates unless they went to UC Berkeley which is also located close Silicon Valley and works closely with many companies there.</p>
<p>@Lemaitre1
So you are saying I should choose SJSU over Cal State East Bay if I plan to stay in the bay for my future career?</p>
<p>The SJSU graduates in greatest demand by Silicon Valley firms are usually Computer Science,Electrical and Computer and Engineering, Physics and Business majors. You should be aware though that unless you are from the SJSU servuce area, which is basically Santa Clara County, your chances of being admitted to SJSU are miniscule.</p>