standard_description: Compute (using technology) and interpret the correlation coefficient of a linear fit.
problem_activity: Task
Is there an association between the weight of an animal’s body and the weight of the animal’s brain? 1. Make a scatterplot using the following data.
{"table": [{"caption": [{"_value": "Body and brain weight by animal. Source:", "a": [{"_attributes": {"class": ["newWindow"], "href": "http://mste.illinois.edu/malcz/DATA/BIOLOGY/Animals.html"}, "_value": "http://mste.illinois.edu/malcz/DATA/BIOLOGY/Animals.html"}]}], "tbody": [{"tr": [{"th": [{"_value": "Animal"}, {"_value": "Body Weight (kg)"}, {"_value": "Brain Weight (g)"}]}, {"td": [{"_value": "Mountain beaver"}, {"_value": "1.35"}, {"_value": "8.1"}]}, {"td": [{"_value": "Cow"}, {"_value": "465"}, {"_value": "423"}]}, {"td": [{"_value": "Grey wolf"}, {"_value": "36.33"}, {"_value": "119.5"}]}, {"td": [{"_value": "Goat"}, {"_value": "27.66"}, {"_value": "115"}]}, {"td": [{"_value": "Guinea pig"}, {"_value": "1.04"}, {"_value": "5.5"}]}, {"td": [{"_value": "Asian elephant"}, {"_value": "2547"}, {"_value": "4603"}]}, {"td": [{"_value": "Donkey"}, {"_value": "187.1"}, {"_value": "419"}]}, {"td": [{"_value": "Horse"}, {"_value": "521"}, {"_value": "655"}]}, {"td": [{"_value": "Potar monkey"}, {"_value": "10"}, {"_value": "115"}]}, {"td": [{"_value": "Cat"}, {"_value": "3.3"}, {"_value": "25.6"}]}, {"td": [{"_value": "Giraffe"}, {"_value": "529"}, {"_value": "680"}]}, {"td": [{"_value": "Gorilla"}, {"_value": "207"}, {"_value": "406"}]}, {"td": [{"_value": "Human"}, {"_value": "62"}, {"_value": "1320"}]}, {"td": [{"_value": "African elephant"}, {"_value": "6654"}, {"_value": "5712"}]}, {"td": [{"_value": "Rhesus monkey"}, {"_value": "6.8"}, {"_value": "179"}]}, {"td": [{"_value": "Kangaroo"}, {"_value": "35"}, {"_value": "56"}]}, {"td": [{"_value": "Golden hamster"}, {"_value": "0.12"}, {"_value": "1"}]}, {"td": [{"_value": "Mouse"}, {"_value": "0.023"}, {"_value": "0.4"}]}, {"td": [{"_value": "Rabbit"}, {"_value": "2.5"}, {"_value": "12.1"}]}, {"td": [{"_value": "Sheep"}, {"_value": "55.5"}, {"_value": "175"}]}, {"td": [{"_value": "Jaguar"}, {"_value": "100"}, {"_value": "157"}]}, {"td": [{"_value": "Chimpanzee"}, {"_value": "52.16"}, {"_value": "440"}]}, {"td": [{"_value": "Mole"}, {"_value": "0.122"}, {"_value": "3"}]}, {"td": [{"_value": "Pig"}, {"_value": "192"}, {"_value": "180"}]}]}]}]}
Do there appear to be outliers in this data? Which animals appear to be outliers? Explain how you identified these outliers.
Removing the outliers from the data set, make a new scatterplot of the remaining animal body and brain weights.
Does there appear to be a relationship between body weight and brain weight? If yes, write a brief description of the relationship.
Take a piece of uncooked spaghetti and use that spaghetti to informally fit a line to the data. Attempt to place your line so that the vertical distances from the points to the line are as small as possible.
How well does the spaghetti line appear to fit the data? Explain.


aligns: no