More electives is not the same as a better academic experience. If you are selecting your MBA on the basis of specialised electives, perhaps you should be taking a specialised masters?

I struggle to think that Bradford has better careers support than Strathclyde, since Strathclyde's outcomes are better. Why do you think Bradford has better careers support?

Other things being equal, I can't think of a reason to select a school with a worse outcome.

Thanks Duncan.

Would you choose Strathclyde over Bradford's MBA? And what's your assessment criteria?

Thanks,

Osama

Well, I think the key criteria for me are the outcomes. First of all, 37% higher salary according to http://rankings.ft.com/businessschoolrankings/european-business-school-rankings-2013

Thanks again Duncan.

Can you help me to understand how certain school has higher starting salaries? In our case, Strathclyde MBA ranking is not far from Bradford. Strathclyde ranks 26th in Europe and 73rd world wide while Bradford ranks 30th in Europe and 95th worldwide. However, starting salary for each is $108K and $84K respectively. Would you please explain how this works from the academics' perspective
.
Thanks,

Osama

Hello all,

In my opinion, one can not come to the conclusion that the graduates of X university earn %something more than graduates of Y University and thus X university has better outcomes just because "average salaries" calculated from the data of a certain time snapshot (and probably a sample?) happen to be so. Even the same applies for various calculations of the same kind at different times give parallel results. This would be a too simplified single variable approach. This is just "descriptive statistics" and can thus be just the starting point of any analysis in terms of "the science of Statistics". To go further to examine the causal relationship i.e. to say "X group earns higher because they have graduated from the University X", one would require a broader data set with additional variables and a more sophisticated statistical analysis. As for the additional variables, these should be decided on by the subject matter experts. Of course, the end result may also verify the initial findings, however this time the conclusion would be a more "informed" one.
Regards,

Hi Osama.

The rankings are a product of the variables outlines in the ranking methodologies. MBA salary is not the only thing in the method, that's why the ranking is not the same as the salary.

Of course sts is not wrong in saying that good outcomes are not the same as high salaries. Primarily, different students have different goals. However, the rankings show that Strathclyde has better students going in and better outcomes going out, year after year, than Bradford. If your outcomes are not correlated with the ones in the rankings, I wonder if an MBA is the right choice for you.

While it's reasonable to say that correlations are not causes, it's worth pointing out that the pool of MBA candidates is very similar across schools, the MBA process is similar, and the important of the measured variables is very similar. It seems massively unlikely that a repeated and consistent divergence in outcomes between those schools is simple randomness.

In my opinion, one can not come to the conclusion that the graduates of X university earn %something more than graduates of Y University and thus X university has better outcomes just because "average salaries" calculated from the data of a certain time snapshot (and probably a sample?) happen to be so.

No, it's really pretty simple, since average salaries are a good indicator of program quality, and of goals met. And since there tends not to be much fluctuation over time (the FT rankings use average salaries as a primary indicator, and don't shift THAT much from year to year) I'd say it's safe to make a few assumptions.

What I tried to explain is not about fluctuation or randomness. Stability in the trends of salaries is no surprise.
I just draw a line between "correlation" and "causation", as Duncan also has rightly recognised in his previous post.

To clarify, let's take an off-the-topic and perhaps extreme example: If you try to analyze the difference between the average wealth levels of "native English speakers" and "native-say-Zimbabwean speakers", most probably you will find that native English speakers are far better off. Based on this, could you come to a conclusion like "native English speakers are better off because of the language they speak"?

Of course, in the case of graduate salaries, universities are not irrelevant as opposed to the example above, however we should still need to consider other possible independent factors that may have an impact on the graduate salaries for a more complete analysis. For example;
- Is there a significant difference between the geographic locations where the graduates of these two universities generally work?
- Is there a significant difference between the industries in which the graduates of these two universities generally work?
- Are there differences in the course ranges of these universities?
-...so on.

Before coming to a conclusion about causation, I would prefer to increase the depth and breadth of my analysis, that is what I say. In the end, you may again find that perhaps it seems only the university that matters, but in this case the analysis would be a more reliable one.

Anyway, if you are satisfied with the comparision of graduate salaries, then of course you may well continue with it.

Regards,

No-one here is making a claim than MBAs produce causation in the manner of the natural sciences. I'm not sure why you are arguing against it.

"...since average salaries are a good indicator of program quality, and of goals met...." (This is about causation. They earn more because they are graduates of a higher quality school)

How do we know this? How do we know that average salaries of one group is higher because of -only- the university?

This is not sufficient to come to that conclusion. Not for or against any argument, I am just in favour of a broader analysis, personally of course.

No-one is saying that one data point is sufficient, only that a repeated occurrence when all the data points are aligned with outcomes is meaningful. If you find someone who says that the only thing you need to look at is salary, please have that row with them.