Quote:
Originally Posted by MarchHare
With a statistically significant sample size, effects like you described are eliminated.
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Not true. Not true AT ALL. I am a system designer for Statistics Canada. When you are first hired into a professional position at STC they send you out on a course where you are put in the field to get to know what the agency does. So even though I work in IT, I was put on the front lines knocking on doors.
First we picked the houses randomly. We then got a list of the people in the house and chose randomly. If that person was not at home we had to come back on 4 separate occasions in order to get the person we selected. We asked the instructor why we had to be so specific - why not just ask the person who answers the door. We were told that if you just gets the person that answers the door you are going to oversample retired people, unemployed people, housewives, etc.. and under sample people that are usually at work, busy parents always off with their kids and people who refuse to answer their door.
On our phone interviews, we will call a random person, and if you say you are too busy we will ask for a time that is more convenient. If you say that you don't know when you will be available, we will wait a few days, maybe a week and call you back. For us it is VERY important that we actually interview the people that we randomly sample because if you don't you introduce bias into your survey. Very few polling companies are as persistent as we are, so there is a lot of inaccuracy in their numbers. They are not getting a true random sampling of the population.
BTW - I was the "dog person". The person that got called upon to knock on the door of the houses that had "Beware of Dog" signs.
This wasn't because the rest of team didn't like me, but rather because I am really, really good with dogs.