new

National Screen Free Week is next week:  Monday, May 2 - Sunday, May 8, 2016!   If you've never participated, imagining an entire week without the tv, tablets, and handhelds can seem incredibly overwhelming.  Believe me, I've been there when we participated for the first time in 2013.  It's not like we didn't do things other than screens, but like most mums, screens were my go-to when I needed a few minutes of peace and quiet - when I needed to not be interrupted every thirty seconds.  Three years ago, I was legitimately nervous about committing to screen free week. I've compiled a list of five tips for getting through your first screen free week based off our previous experiences.  I hope you'll find it helpful and expand on the ideas (share them with me too!) to create a week long batch of fun, screen free memories! 1. Reflect on the fun things you did when you were a kid Pretty much guaranteed, the things you remember being the most fun when you were a kid di

I was inspired by Ginny of 1000 Hours Outside blog and instagram account last year in early spring and I have not been able to get the idea out of my head.  So this year, as part of my 100 small things list , I included attempting to log 1000 hours outside as a goal.  I made this a personal goal after going back and forth and trying to figure out if it was going to be a goal for the kids or our family as a whole - but I started questioning myself about then how would I determine if time counted?  What if one kid wasn't with us because they had school, or practice?  So I settled on the goal being my own personal goal - most times the kids are with me anyway, but if I take the dogs for a walk alone, or a I steal away some morning sipping coffee on the front porch while everyone sleeps in - those are my counted hours. In logistical terms, I try my best to start my cellphone timer when I go outside and then pause it and start again during the day as needed.  At the end of each day, t

The aim of the logistic regression is to build a model for predicting a binary target attribute from a set of explanatory variables (predictors, independent variables), which are numeric or categorical. They are treated as such when they are numeric. We must recode them when they are categorical. The dummy coding is undeniably the most popular approach in this context. The situation becomes more complicated when we perform a feature selection . The idea is to determine the predictors that contribute significantly to the explanation of the target attribute. There is no problem when we consider a numeric variable. It is either excluded or either kept in the model. But how to proceed when we handle a categorical explanatory variable? Should we treat the dichotomous variables associated to a categorical predictor as a whole that we must exclude or include into the model? Or should we treat the each dichotomous variable independently? How to interpret the coefficients of the selected dichot