the results of a survey where they asked students "Are you happy at your school?"
It is interesting, in the sense that it is a statistical anomaly, that three of the five "unhappiest" schools are affiliated with the Catholic church.
It would behoove the management to do a deep-dive to get more resolution on that anomaly.
Jumping to conclusions
Suppose you worked for a large automotive manufacturer and for "career development" purposes you were routed through "Marketing".
In the course of evaluating survey responses from customers for a product you had been intimately related to, you stumble across this response from a customer in Illinois "The vehicle leaks when the windows are open and it is raining."
If you were too lazy to call that customer and interview them, what conclusion are you likely to have drawn? "Drivers in Illinois are idiots."
And if you drew that conclusion a priori, what are the chances that you would make that call?
The rest of the story
The driver was not a moron. He worked in the financial industry in Chicago. He paid a substantial premium to purchase the convertible version of the model.
His complaint was that the spacing of the roof bows, the cut of the door line and the lack of a rain gutter on the side of the roof funneled a torrent of rain-water onto his lap when he paid tolls on rainy afternoons.
He would look at the weather forecast and drive his sporty convertible to work when no rain was forecast. Sometimes the forecasts were wrong.
In the days before Speedy-pass, every driver had to leave the toll-road, roll down their window and pay a toll. Even if there was a roof over the wealth-shake-down station, rain continued to sheet off of the roof.
Not only did his dry-clean-only wool suits not like being drenched, sometimes he was on his way to see a client. Looking like you wet yourself with urine is not conducive looking professional.
The original survey did not have a box for the financial professional to fully communicate the information he wanted to pass along.
People are often unhappy when there is a gap between expectations and reality.
Did the school promise something they could not deliver? That is relatively easy to fix. Stop making those promises even if it means fewer students apply for enrollment.
Examples might include a smaller school promising all kinds of clubs that would welcome...ah...students of the 157th gender when, in fact, those clubs did not exist. Or perhaps a school that promised a vibrant and diverse student night life when the community around the school is a war-zone after dark.
Did the students go to the school expecting things that the school never promised? That might be more difficult to address.
Examples might include students expecting high grades for minimal effort. If that is the case, then unhappy students is evidence that the schools are maintaining high academic standards and that is a GOOD thing.
The point is, the survey question was too broad and too non-specific for diagnostics.