Estimating Aurora – 36.235 million points
I tried to use some Maths and some educated assumptions to estimate if we will manage to achive the overall goal of 36 million unique… Read More »Estimating Aurora – 36.235 million points
Ingress
Ingress related blogs
The Aurora Glyph Hack Challenge – planning ahead
Today the Aurora Glyph Hack Challenge was announced. Personally, I think the challenge is great. I managed 793 different portals during the Myriad Hack Challenge.… Read More »The Aurora Glyph Hack Challenge – planning ahead
Investigating level 1 portal key and glyph hacks
One of the most often asked questions for new players seems to be accurate data on drops from hacking portals. There is some research scattered… Read More »Investigating level 1 portal key and glyph hacks
Prime Day Part 9 – Summary, speculations and reflections
If you have read everything I have presented, then you likely will understand why I strongly believe that Niantic used the faction ownership (Resistance, Enlightened… Read More »Prime Day Part 9 – Summary, speculations and reflections
Prime Day Part 8 – revisiting an older analysis
My original analysis was done pretty directly after the event. I generated the following plot: I presented a write-up here: https://www.reddit.com/r/TheSilphRoad/comments/9vdjix/analysing_dirty_data_why_i_believe_the_actual/ This early data got… Read More »Prime Day Part 8 – revisiting an older analysis
Prime Day Part 6 – looking at binomial distributions
In part 4 I outlines why it is important to look at individual slices of the data as lumping all together would diminish the signal.… Read More »Prime Day Part 6 – looking at binomial distributions
Prime Day Part 7 – a chi-square test of 1.4E-24
We are back to lies, damn lies and statistics. We are now looking at chi square tests to analyse how well our data distribution fits… Read More »Prime Day Part 7 – a chi-square test of 1.4E-24
Prime Day Part 5 – looking at lucky and unlucky players
In the last part I argued that lumping all data together would diminish the signal we get. Statistical tools allow us to look at a… Read More »Prime Day Part 5 – looking at lucky and unlucky players
Prime Day Part 4 – avoiding a catch 22
So how would we analyze the data? Let us start with the observed rate of Cubone and Ponyta and work backwards. Unfortunately this generates a… Read More »Prime Day Part 4 – avoiding a catch 22
Prime Day Part 3 – would this fit with Ingress data?
What happens if we approach it from the Ingress point of view? Indications and clues The data we have Niantic announcement – colors linked to… Read More »Prime Day Part 3 – would this fit with Ingress data?