The example graphs i used were form a blog that had a NY Times posting on it . the graphs indicates how family house hold income can effect the student testing abilities. The data had proven that the students with an higher source of income is more likely to pass the SAT with a higher grades than the student who comes from a not so wealthy home. This graph also can relate to my major because in my career i would be dealing with families that are less benefit and that are effected physical , emotionally, and mentally due to them being less fortunate .
My Laptop was giving me trouble copying and pasting the graph so i just add the link below :
http://economix.blogs.nytimes.com/2009/08/27/sat-scores-and-family-income/?_r=0
Its actually funny because I was looking at a similar graph towards this and decided to opt out. Graph shows a lot of valuable information, like the direct correlation between incomes and sat scores from all around the city. I actually thought that kids who had money did worse than your average kid from the urban community being that kids who are born into money or have parents with really stable jobs seem to be a bit inattentive and lazy, not saying that since its the other way around kids from the urban community are lazier etc.. Good graph!
After reading your article , I found it to be some what true because my SAT score and family’s income match the relationship of the income of families to SAT scores graph from the article. But then again there are many stories of kids in middle class income that achieve a perfect SAT score and get recognized from ivy college. I thought you did a good job describing the graph and how it relates to the article .
I found this graph extremlyintresting , because its says a lot of the “equal ” opportunity slogan of this nation, when in fact there not equal because of so many unfortunate factors that lead to or aid in failure to obtain those equal opportunities.
I found this graph extremlyintresting , because its says a lot of the “equal ” opportunity slogan of this nation, when in fact there not equal because of so many unfortunate factors that lead to or aid in failure to obtain those equal opportunities.
– Anne Duchemin
I found the most interesting part of this article to be a comment from Elliott
Smith: “The R-square value is very misleading. The .95 is the R-square predicting the test score *means* from income category, so it is inflated by aggregation (i.e., all the variation of scores around each mean is omitted). The actual correlation between an individual’s score and family income is probably closer to the .2 range.” The point is that statistics is a tricky tool and it is very easily miss used. Which is not too minimize the unjust nature of the income stratification which has gotten progressively worse over the last few decades.
I found the most interesting part of this article to be a comment from Elliott
Smith: “The R-square value is very misleading. The .95 is the R-square predicting the test score *means* from income category, so it is inflated by aggregation (i.e., all the variation of scores around each mean is omitted). The actual correlation between an individual’s score and family income is probably closer to the .2 range.” The point is that statistics is a tricky tool and it is very easily miss used. Which is not too minimize the unjust nature of the income stratification which has gotten progressively worse over the last few decades.