I'll be back in two minutes - what did I miss?

So there's a UFO right in front of you: what do you do? Should you get the camera, phone a friend, or seek shelter in the bunker you bought from Danoz Direct one late night?

Well you don't have much time make the decision. Half of reported UFO sightings lasted for two minutes or less (Figure 1). And 90 per cent lasted for six minutes or less. 

Figure 1

This would barely give you enough time to cook a quick snack. But it would give you plenty of time to take your phone out of your pocket and snap a quick photo. Some people did this, apparently. About 5 per cent of the statements given after reporting a UFO sighting mentioned the word camera. None of the reports mentioned guns, bunkers, or two minute noodles.

The length of sightings has become slightly shorter over the past two decades (Figure 2). I don't think this means too much. But it does give me an opportunity to put a moving gif on the blog. I guess if you squinted you could say that this gives some evidence that the speed of UFOs has fractionally increased in recent years, which would be consistent with a rise the speed of  military aircraft over the period. But this could be bending the data.

Figure 2

Next post, the UFO research will reach a pinnacle with the release of a killer graph. Perhaps it will be so big that I will coincide it's release with Independence Day. A day that will forever be remembered for alien invasions.

Technical stuff

Despite the post's apparent simplicity, getting the unstructured data into a workable format was a pain. In the end, I parsed it using the tm library. But in hindsight it would have been easier and more efficient just to use R's base string functions. I made the graph of the dancing density function using the animation library, which was actually comparatively easy.

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Summer has came

It's getting hot over there, so hot, I want to see some UFOs, I am getting to hot, I want to see some UFOs   

— Not quite Nelly

Summer is here (well in the US — in Australia, it's winter). And along with the rise in the temperature, comes a rise in reported UFO sightings (Figure 1). Just like our 'day of the week' analysis, this finding is statistically significant at any reasonable level.

A keen observer would note that Figure 1 is missing some key information. Namely, that the 'summer effect' could be due to one particularly active summer, rather than a consistent reoccurring pattern each year. That is why we need to look at the time series of the number of reported UFO sightings (Figure 2). Glossing over this series shows clear evidence of seasonality. Decomposing it, reaffirms this finding (see technical stuff). 

The time series also tells us the the number of reports has been trending up since the early 90s. And the growth in the upward trend has been faster than growth in US population (Figure 3).

 

Tying all the results together reaffirms earlier findings (apologies for some repetition). People are more likely to stay out late and drink more in the summer. While the upward trend likely relates to an increase in the ease of reporting sightings, a fall in the stigma related to reporting sightings, or biases in how the data are collected. There are also some large movements that, provided the demand for UFO information remains high, I will look at later.

Next post, “Ma... Ma… there's big ole shiny fing in the sky. Will there be 'nough time to get the camera and shotgun? Or would it be best if I just got the shotgun?” — We look at how long UFO sightings tend to last for.

Technical Stuff

Ideally, I would seasonally adjust the data using x13 from the US Census. This is basically an ARIMA specially designed for seasonal adjustment. But I can't get this working with Ubuntu — this didn't help. So for the time being to look at the seasonal components you'll just need to make do with a decomposition (Figure 4). Simply put, this process splits the data into three components, a trend, a seasonal, and an irregular.

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