Shielding of Electrosmog: Some Observations (part 10)
The effectiveness of orgonite as a method of protecting against cell phone RF EMR: today I reveal the results of a refined experiment with two big lumps
Back in part 9 I was cut short in full flow, as it were, restricted both by the length limit set by Substack and the time limit set by Mrs Dee. These days I can no longer spend 50+ hours per week wading through data at my leisure for I have businesses to run. I had hoped my Substack venture would attract sufficient subscribers across three publications to give it priority in my life but this turned out not to be the case, and so I find myself juggling for whatever free time I can muster. This morning all chores have been done, my businesses have been attended to and there is a promise of rain… so here I am with a cuppa at my keyboard once again.
Something funky was going on back in part 9, in that we thought we’d spotted a significant impact of two large lumps of orgonite but that significant impact turned out to be statistically insignificant. I blamed this on the bunching of extreme values, but we better go back and look at the raw data without delay.
Here’s a time series of those 2,400 per second values with the eight observation periods marked by dashed grey lines:
Aha! And there we have it. The phone went bonkers when first switched to transmit mode (phase 3) but then settled down into a sparse pattern that looks rather random. The phone wasn’t jabbering away constantly: this is a mightily important consideration for any analysis of means and medians, regardless of statistical technique, will rest on the assumption of underlying constancy of the signal source. Because this isn’t constant we can’t go saying anything decisive about the impact of orgonite. It’s worth noting that this isn’t how my phone normally behaves – it usually chatters away more or less constantly until flipped back into aeroplane (you can see this for yourselves by squinting at back issues). I have no idea why my phone went into sporadic mode for this experiment but it sure has messed things!
That bunch of big spikes between 14:17 and 14:18 will have inflated the mean for this phase, and absence of similar during the following orgonite phase may or may not be due to the shielding effect of this substance; it could easily be due to lack of WhatsApp activity! If I were an unscrupulous retailer of orgonite I’d be able to claim scientific proof that my wares were worthy, and very few folk would be any the wiser.
One way to crack this is to let the phone settle for several minutes before observation begins and switch repeatedly between two 5-minute phases – transmitting without orgonite and transmitting with orgonite. Another way to crack this is to put a constant RF EMF source on the kitchen table. After three pieces of particularly yummy flapjack I realised I possessed such a source – my Wi-Fi router. But, TBH, a router ain’t a phone, so today I’m going try the repeated phase method.
Method
Yer kitchen table setup exactly as described in part 9. The phone was flipped into transmit mode and allowed to settle for 10 minutes before data recording began. I opted for six paired periods starting at 15:00:00 on Saturday 20th September, this giving a total sample of 3,600 per second records. As before the first and last 10 seconds of each phase was excluded, this bringing the sample down to 3,360 records half of which were the transmitting phone alone and half of which were the transmitting phone with dirty great lumps of orgonite strapped to the back.
Before the EMF-390 started recording data I flipped it into a graphical display mode to enable me to eyeball the per second values as they trundled along. I’m sure glad I did this because it revealed interesting detail I hadn’t noticed before: the phone would churn out RF EMR for a while then suddenly stop until I either moved it or popped it out of screen saver. This suggests that the phone is trying to determine periods when it can save battery. Whilst this is a good thing it does mean that the algorithm will play havoc with data collection, coz different observation phases could easily be subject to differing numbers of idle periods. To circumvent this potential source of bias I decided that the logical step would be to further exclude all data records where the RF EMR signal hit the detector system minimum value of 0.001 mW/m².
Let’s take a look at what transpired…
Results
We shall start with the sample size to ensure all is well with coding…
..yep, all is well with coding. And now for a count of zero transmission periods by phase: