Statistics

[crenca]

Just to pile on to what others have already said, it's all about expectations. I have had my bronco for about 5 weeks now. About week 2 the right passenger window started "creaking" when rolled all the way up, so I don't roll it all the way up (leaving it down 1/8 inch). I read here that I would start troubleshooting with a window reset procedure, but that apparently takes holding a button for 10 seconds...twice...I have not even bothered. Even if/when I decided to put in any effort to this, I can't even imagine taking it to a dealer for them to hack on it, I would just hack on it myself with weather striping from Walmart or some such

Now I admit my wife would have much preferred for me to have purchased a 4Runner, but even she admits that if you stay off the interstate the noise level in the Bronco is "bearable". Now her Sequoia? That thing has to be quiet, and we have had a mechanic (not dealer) work on that for noises the Bronco makes when it's just parked and engine off.

I fully expect to have to put some real time and $ into the top when it de-laminates, leaks, or whatever it is going to do 6 months or 6 years from now, but I wanted a soft top anyways

Thing is, Ford and their dealers are all too happy to sell to customers who have expectations that the Bronco is something other than it is. The complaining is worth it to them I assume.

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[WeyanGe]

Using Python to scrape forum data for statistics on Bronco roof issues is a practical way to start. To assess whether the frequency of these posts is genuinely significant, you might find https://www.gigacalculator.com/calculators/p-value-significance-calculator.php helpful. I’ve used it to check statistical significance in other contexts, and it makes analyzing A/B test results or comparing groups pretty straightforward.

 

[Area51BS]

While it won't help convince anyone, you can pull the data "fairly" easily if you can code and willing to spend a few days (up to a few weeks depending on your skill) narrowing down results. You can write a python script to "scrape" data though any website - for example the B6G website, basically program it to run through every post and search for some combination of "roof" & "leak" or "crack" or "issue" etc. Then divide # of posts with these keywords over total posts.

As a learning exercise in data scraping with python, this would actually be a fun "real world" example where you continually debug the code and enhance the efficacy of the script, vs the boring crap they have you scrape in python courses. The hard part would be deciphering which posts are related to issues, vs just mentioning the top. But that's where the hard work comes in to narrow down the results properly.

If it's something you're wanting to try, I suggest using Microsoft VSCode with the built-in python and Jupyter Notebook extensions, as well as adding the Co-Pilot AI "enhancement" extension.

At work, we use python web data scraping on dozens of our applications. It takes some time to set up properly, but once it works it's pretty cool.

Nope. Rather drive my floppy top. We will leave it to you at work!

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