[Galaxy S III General] Jarmezrocks:
[MENTION=2872010]rootSU[/MENTION]

This started out as a long PM but seeing as though private messages are full XDA says that you cannot receive any more emails until you clear your inbox, just thought I would share some recent discoveries for you to analysis and make best of what you will?:good:

Hi I read your post you contributed in the S3 section and I am aware that you are now a note user.

This isn't a support question either; for your interest I would say that I think of my self about the same as what you probably do of your self and possibly with much similar skills or level of technical understanding? So I wouldn't say this is an uneducated contact message either? ;)

Anyway, I have an S3 LTE and naturally the 4G LTE is going to zap a bit more power when comparable to that of non-LTE device; obviously there are many many other un-constant variables that have a direct relationship with power charging and battery consumption. Many other factors might also need to be considered that might otherwise aren't but probably should be, such as device age, temperature (with temp comes resistance, with resistance comes increased power consumption....which left unaddressed can lead to further temperature increases and so on and so forth.

One this I did study at university was stats:) So when it comes to testing standard error or test samples etc, I am aware that it becomes almost impossible to get everything constant between devices, between Tests them selves, or even between operators.

I don't disagree on your posts or theory about this in the thread either, nor Dianne's explanation on how the statistics are generated on the device. That makes perfect sense to me. However what could be a factor that many users who aregue against the ideal of how and what battery stats is and how its influenced, is randomized distribution and large variance over the battery sample duration. You may need to think that last sentence through a few times to see how that piece of the jigsaw puzzle fits within your topic of discussion.

Largely I think what could be happening with most devices and observed by device users could be related to skewed data or abnormal distribution....actually I would put money on it that this IS the cause of peoples apparent battery increased consumption.

When you think about what is happening directly after flashing firmware and how a device is responding to data input and generation it becomes clearer why it is occurring. Now some things to consider (you no doubt would have considered these long before me and you probably going to say 'Yeah buddy whats new? Get to your point') are this: Say a wipe is performed on a device when new firmware is installed. The original known location of the battery on its scale between 0 and 100 is lost. The battery gauge (yes gauge not stats) has no real bearing or understanding of where it is in relation to 0 or 100 does it? But as time goes by the sample size pool increases. So we have two relationships happening inverse to each other. 1) Battery consumption depleting over time 2) Battery statistics sample size increasing over time. One would think and assume that over the duration of the time and use cycle for one battery charge that the battery gauge should be returning a more accurate reading...right? Why then is it not? That is the question many users are asking and it is with this that the assumption of the sample statistics is wrong (i.e The data is **** so lets wipe it) when really we need to be increasing the sample size to make it more accurate.

Ok the next phenomenon that I feel is less talked about and probably not well understood given the typical conditions after new firmware is written to the device. Some things I can say are typical and I guess you can say with what I have discovered more recently that they are variables that can be safely ignored. 1) I will mention it now to get it out of the way and that is user configuration. I don't mean did this guy set up his fresh device right or wrong, what I am talking about are relationships and changes in data....that would "un-normalise" a sample set. What I mean is when someone flashes a device with new firmware they are usually spending time setting the device up and re-configuring it again this could follow the same relationship as battery consumption its self being at state 0 the settings are unoptimised and the user is actively using the device with the screen on and consuming likely a lot more than normal for a good duration of its "user up time"...possibly at some point settings are more optimised (this brings a point of error in here but we should in this case disregarded for the time being. I digress the phone becomes more optimised as the battery becomes more dead, right? You should agree here :) What else is happening? What apps are running and what variables are those apps reading? Which leads to what actions are those apps doing in response to the measurements they are reading? hmmm that's a good question most people haven't thought of before? What about standard inbuilt Android kernel related settings and adjustments, like reducing screen brightness when battery is below 10% and things like that......wait a minute! That means apps are making decisions directly relate to OS performance based on their current readings.....which could be wrong! What happens when the kernel throttles power when it shouldn't? This affects the battery on duration! More variation!

So now my weird battery scenario. Say I have an opportunity to increase my statistical sample size. What happens to the experiment? Ok better still 'what the heck do you mean by increase my sample size?' you may ask? Well say for instance (and this is true) I have 3 batteries and pretty much there is always one present at full charge no matter what. That is the case in my situation. Just so happens to be that I have been repairing a few Galaxy S3 phones over the last few weeks, hardware faults, sudden deaths and all sorts of failures etc, not to mention that I have my own S3 LTE stock phone and my S3 LTE test/developer device (which often is used more than my stock phone because of its features) anyway I have for the last few weeks always had at least 3 batteries on rotation. What does that do to statistical analysis? Well seeming I can essentially use my phone continuously the battery stats has had plenty of time sampling and no time charging what so ever. My phone stays on over night and I don't plug it in unless it needs to (maybe one day I might convert Chainfires code for NoMoarPowah??? haha). What happens then when you increase the sample size but you increase the variance? Variation between tests? Well I did this too! How? Well mid way through I decided to flash a port I am working on which failed miserably anyway. Bootloops. But I had a nandroid backup. So during that period of time battery was being consumed that was not being registered to the battery stats sample pool. I then restore the device back to its former original state. The battery was just about dead.....or was it? That was the confusing part.....I could no longer trust the display as the gage was not reporting what the actual battery measure was at that time. I always run my device dead anyway....not dead dead (as I hear that is not good to do to lithium batteries? (that could be a new Myth to go bust man!) but when it switches off due to not having enough power then I put it on charge. Right....but in my case there is no "charging" as such, just a new battery thats 100%.

Now get this part.....my phone for the past hmm I dunno 6 or 7 hours has been reading 0% battery. Yep big red exclamation mark through the battery symbol and everything, but I can pick it up right now and push any button and it will wake up the screen. I can surf the web I can do all the **** you usually freak out about not doing when you get that low on battery. So now...what has the android resource monitor done to my performance now that it "thinks" I am so low on battery? I'd say it would be throttling the thing, reducing the number of cores and slowing the clock down even further. So now I am going to wait for it to die and get back to you

EDIT: I have my answer just before I finished this long arsed message lol timing haha. I decided to check my battery "stats" (yes I mean stats not gauge) and I managed to take two screenshots before it finally gave up and shut down. Man you are going to love these when I upload them haha.

I am not exaggeration when I say how long I was sitting on 1% hahaha