Observational Study Data Set

Who: Cold Cereal 
What: Price and Nutritional information
When: January 2005
Where: Albertsons' Online Store
Why: To analyze the relationship between price and sugar content.
How: Using R, I generated 15 random numbers from 1 to 249 because there were 249
	diffent items under the cold cereal section of Albertsons Online store.
	sort the cereals alphabetically and number them from 1 to 249.  If the cereal's 
	number is in the set, then collect its information.  You end up with a sample of
	cereal that Albertsons sells.
	My 15 random numbers:
		> sample(1:249, 15, replace=FALSE)
 		[1]  33  53 227 179 191   8  74 166 243 158 136   1 190  19 198

Number of observations: 15 
Variable Names: 
Name: Cereal name
Brand: Cereal brand/distributor
Size: Amount of cereal in box measured in ounces
Price: Cost of cereal measured in dollars
Serving Size: Serving size measured in cups
Calories: Calories per serving
Total Carbohydrate: Total carbohydrates per serving measured in grams
Sugars: Sugars per serving measured in grams

With this data set, we can explore the sugar-to-total carbohydrate ratio of cereals and see
how that is related to price.  Another factor that can affect price is the brand or 
distributor of the cereal.  Generally, name brands are more expensive than generic brands.
When dealing with brands, a dummy variable will need to be created where 1 indicates a name
brand and 0 indicates a no name brand.  Another variable to be considered is how the calorie 
count comes into play.