So Conservatives hate babies? Wow, the whole world would be progressive if that were true. There might actually be a lot more progressives if they didn't support killing their unborn children however.
Really? I don't need a dictionary reference, thanks. Let me slap the dictionary right back at you...."Statistical validity refers to whether a statistical study is able to draw conclusions that are in agreement with statistical and scientific laws. This means if a conclusion is drawn from a given data set after experimentation, it is said to be scientifically valid if the conclusion drawn from the experiment is scientific and relies on mathematical and statistical laws." This isn't about measuring a central tendency....it implied and drew false conclusions based on limited information and little relevancy. . An cutesy little graphic with political overtones that may or may not be the causation for their conclusions. This is precisely WHY averages are mostly useless other than conversational or in terms of understanding the normal distribution of the Bell Curve. They are not useful when a distribution is heavily skewed at one end, with a small number of unrepresentative outliers pulling the average in their direction.
This is true, but this is hardly recent news and there are a dozen articles out there with supporting information from nonpartisan sources like the CBO. It's not just true, it's laughably true. I understand not wanting to believe it because that would mean all of those voters were hoodwinked into voting for people who support positions that negatively affect their constituents. That doesn't say much really for the people who elected them.
Well, you mentioned "normal use of the word". Is there some definition that I'm unaware of? I still think it is perfectly applicable. I disagree and thought they backed up their thesis quite well, exactly as your definition states. You chose to post it instead of the more scientific scatter plots that they also offered. The numbers they cite are not political. They are numbers. Not all data fits a bell curve. Moreover, averages are extremely useful and have been for millennia. To simply disregard their data by characterizing averages as "useless" is an unconvincing argument.
Not when a specific variable within the data shows the exact opposite of what is drawn from the conclusion. Their conclusion was errant and outside of a number of other variables that might have been the causation. I posted the graph specifically dealing with averages and exactly why they tell us very little and certainly nothing scientifically useful. Disagree. If it doesn't, it's been manipulated. The curve may be flat or narrow but it's still present. I said "mostly useless". In terms of fun consideration and general directional information, yes. In terms of anything truly useful or verifying cause/identifying variations, they don't do shit. "Averages can be misleading if considered in isolation, because the average of a highly variable distribution tells us little about specific outcomes we're likely to encounter. There's the old joke about the person who couldn't swim but confidently entered the water because it averaged only 3 feet in depth. Or, more crudely, there is little information in the truism that the average person has one breast and one testicle."
