animal gestation longevity

baboon 187 20

bear, black 219 18

bear, grizzly 225 25

bear, polar 240 20

beaver 122 5

buffalo 278 15

camel 406 12

cat 63 12

chimpanzee 231 20

chipmunk 31 6

cow 284 15

deer 201 8

dog 61 12

donkey 365 12

elephant 645 40

elk 250 15

fox 52 7

giraffe 425 10

goat 151 8

gorilla 257 20

guinea pig 68 4

hippopotamus 238 25

horse 330 20

kangaroo 42 7

leopard 98 12

lion 100 15

monkey 164 15

moose 240 12

mouse 21 3

opossum 15 1

pig 112 10

puma 90 12

rabbit 31 5

rhinoceros 450 15

sea lion 350 12

sheep 154 12

squirrel 44 10

tiger 105 16

wolf 63 5

zebra 365 15

Our dataset contains the following variables:

animal: the name of the animal species.

gestation: the average gestation period of the species, in days.

longevity: the average longevity of the species, in years.

Select all of the data in columns B and C, and then in the Insert tab choose Scatter in the Charts group.

Choose the first scatterplot option (Scatter with only Markers).

Click in a cell outside of the first three columns of data.

Type =correl(B2:B41,C2:C41)

Scroll down to row 16 of the data. You will see that this contains the values of the variables for the elephant.

Click on the row header 16 to select the entire row of data.

Right-click and choose Delete from the pop-up menu to delete the row.

You will see that the values of the variables for the elephant have been removed from the data. Notice also that the correlation between gestation and longevity has changed.

Question 2:

Report the new value for the correlation between gestation and longevity and compare it to the value you found earlier when the outlier was included. What is it about this outlier that results in the fact that its inclusion in the data causes the correlation to increase? (Hint: look at the scatterplot.)

In the last activity, we saw an example where there was a positive linear relationship between the two variables, and including the outlier just "strengthened" it. Consider the hypothetical data displayed by the following scatterplot:

scatterplot where the dots are loosely clustered at the upper right part of the graph

In this case, the low outlier gives an "illusion" of a positive linear relationship, whereas in reality, there is no linear relationship between X and Y.