MacMillan,+J

Brain storming obecity overweight unhealthyness healythyness intelligence marks grade point average schools

healthyness effect intelligence? yes what affects marks idoes inteligence effect marks yes and very subjective does healthyness effect marks healthyness too hard to define obecity effect individual marks? individual marks too hard to find data on individual obecity rates too hard to find data on

Question

Are the average marks of schools affected by the average students in the school that are overweight.

begginning Hypothesis

I believe that schools with a high average amount of students that are overweight will, have a lower grade point average.

PHASE 2

links thus far

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Hypothesis: I believe that there will be a moderate positive correlation between obescity and grade point average.

Reasoning: I believe this will be because people that are obese have a higher chance of heart disease along with a variety of other serious medical conditions. These medical conditions could have a serious effect on concentration and ability to preform academically.

Potential Bias: There is a strong possibility for sampling bias, along with extrenuos variables. Sampling bias could come from only taking samples from one culture, or area of people, extrenuos variables could come from things such as poverty and general culture of the people involved.

New topic

Question: does being overweight / obese effect the perceived mental health of a person?

hypothesis: I think that being overweight / obese will strongly negatively effect the mental health of a person.


 * || 2003 || 2005 || 2007 || 2008 || 2009 ||
 * NF ||  ||   ||   ||   ||   ||
 * Good Mental || 72.2 || 79.8 || 75.2 || 77.5 || 70.7 ||
 * Poor Mental || n/a || n/a || n/a || n/a || n/a ||
 * Overweight / obese || 26.3 || 36.7 || 46.7 || 35.0 || 47.3 ||
 * PEI ||  ||   ||   ||   ||   ||
 * Good mental || 76.0 || 76.8 || 67.1 || 78.3 || 73.2 ||
 * Poor mental || n/a || n/a || n/a || n/a || n/a ||
 * Overweight /obese || 28.8 || 43.0 ||  ||   ||   ||
 * NS ||  ||   ||   ||   ||   ||
 * Good mental || 79.0 || 80.2 || 76.8 || 74.3 || 75.3 ||
 * Poor mental || 7.3 ||  || 5.4 ||   ||   ||
 * Overweight /obese || 28.3 || 33.3 || n/a || 26.3 || 29.0 ||
 * New Brunswick ||  ||   ||   ||   ||   ||
 * Good mental || 76.2 || 76.5 || 77.7 || 75.9 || 71.8 ||
 * Poor mental || 4.5 || 2.5 || n/a || 7.7 || n/a ||
 * Overweight /obese || 24.3 || 32.2 || 34.3 || 27.7 || 25.6 ||
 * Quebec ||  ||   ||   ||   ||   ||
 * Good mental || 80.2 || 77.4 || 80.7 || 83.1 || 78.1 ||
 * Poor mental || 2.5 || 2.7 || 2.5 || 1.7 || 1.7 ||
 * Overweight /obese || 16.8 || 21.3 || 18.3 || 27.2 || 22.5 ||
 * Ontario ||  ||   ||   ||   ||   ||
 * Good mental || n/a || 76.2 || 76.3 || 77.4 || 77.4 ||
 * Poor mental || n/a || 3.4 || 4.5 || 4.3 || 3.7 ||
 * Overweight /obese || n/a || 22.5 || 20.9 || 27.2 || 25.4 ||
 * Manitoba ||  ||   ||   ||   ||   ||
 * Good mental || 76.8 || 76.6 || 76.6 || 74.9 || 81.6 ||
 * Poor mental || 2.8 || 3.4 || n/a || n/a || 4.2 ||
 * Overweight /obese || 22.8 || 17.3 || 39.9 || 30.1 || 29.9 ||
 * Saskatchewan ||  ||   ||   ||   ||   ||
 * Good mental || 75.2 || 76.0 || 78.3 || 78.1 || 76.8 ||
 * Poor mental || 4.0 || 3.5 || 2.4 || 2.2 || 3.7 ||
 * Overweight /obese || 22.4 || 31.8 || 27.4 || 28.7 || 20.7 ||


 * Alberta ||  ||   ||   ||   ||   ||
 * Good mental || 77.1 || 77.4 || 78.9 || 75.9 || 81.5 ||
 * Poor mental || 4.3 || 4.9 || 5.5 || 2.8 || 3.3 ||
 * Overweight /obese || 21.7 || 23.7 || 24.0 || 17.2 || 25.4 ||
 * British Columbia ||  ||   ||   ||   ||   ||
 * Good mental || 71.9 || 77.5 || 75.1 || 80.9 || 73.8 ||
 * Poor mental || 4.1 || 4.8 || 3.5 || 2.2 || 3.1 ||
 * Overweight /obese || 18.8 || 24.2 || 17.2 || 20.0 || 27.2 ||

The mental health in good condition data is has surprisingly little deviation at 2.90

the obesity / overweight data however had a higher standard deviation at 7.12

The correlation coefficient of this data is -0.23522, this is obviously much lower than I expected. This is probably due to this being a study of the full population rather than a controlled group, this allowed bias and large numbers of more "average" results to skew the data.





Bias: There is a great deal of opportunity for this data to be biased. As I said before this data is from a census, rather than a centralized study, this allows for a strong non response and response bias. This is because in the census there is no motivation to answer truthfully or at all. Beyond that bias there is also the fact that there are a huge number of variable that go into a persons mental health. For this data to be accurate a full study would have to be performed with not a greater audience (being that this is a census) but a smaller one, for greater control and to limit the extraneous variables that are present currently.

Conclusion: My hypothesis was incorrect and with a correlation coefficient of -0.23522 my data is ultimately inconclusive. This is because the coefficient is relatively low and there is a relatively high possibility of bias.

@http://cansim2.statcan.gc.ca/cgi-win/cnsmcgi.exe?Lang=E&CNSM-Fi=CII/CII_1-eng.htm (accessed: January 16, 2011)
 * Source:** Statistics Canada. //Table 105-0501 - Health indicator profile, annual estimates, by age group and sex, Canada, provinces, territories, health regions (2007 boundaries) and peer groups, occasional//, CANSIM (database).