Logistic regression

The next data-analysis method I'm playing with is logistic regression (LR).

It's a method often said to be included in a field of statistical computing (called machine learning, statistical learning, artificial intelligence, data mining, unsupervised learning, etc). LR is mostly used in cases of yes/no classifications.

I'm trying to use data from my previous blogs where possible. So the dataset is not really super suitable for LR (I don't believe I could really use the model result to predict the probability of future undisturbed nights of sleep) - but I'll use it anyway as a data-exploration tool. The data are taken from camera imagery of our baby/toddler's sleep each night (see earlier blog posts).

It is probably possible to estimate, by eye from the red crosses, that there have been more undisturbed nights of sleep in the later months. But the logistic regression makes it clear that there is a positive relationship - i.e. our baby/toddler is sleeping through more and more nights (apparently sleeping through most nights by the end of the year).

The sit-and-reach test

Some conclusions:

1. Youth and females have greater flexibility than elders and males (perhaps obvious).
2. For my group (33-year-old males) the 50-50 point by coincidence is '0 cm', i.e. touching one's toes. Meaning that about half cannot reach their toes (although 80% of young girls can!). 
3. As for my own story, I used to be 13 cms short of my toes. This meant that I was at about the 20% mark (4 out of 5 men could reach further than I could). BUT NOW, after weeks of exercise, I can exceed my toes by 7 cms - this means that I am over the 60% mark and only 2 out of 5 men can reach further than I can!

Data source: http://www.exrx.net/Calculators/SitReach.html
Image source: http://oncourt.ca/news/wp-content/uploads/2013/05/1.jpg