GRE Data Interpretation

GRE Data Interpretaon

Quesons 1-3 are based on the following graph

1. If Madagascar’s exports totaled 1.3 billion dollars in 2009,approximately what was the al!e ,in

millions of dollars, of the co!ntry’s exports to "hina # $.%2 &. '( ". 100 ). 32% *. %20 2. +hat is the approximate rao of Madagascar’s total exports to -rance, the /, ermany, and "hina combined compared to Madagascar’s exports to all other co!ntries# $. 2% &. 12 ". 23 ). 32 *. 21

3. If Madagascar’s exports to -rance increased to 33 of Madagascar’s total exports in 2010,by approximately what percent will exports to -rance increase as a percentage of all exports between 2009 and 2010# $.   &. 1 ". 32 ). (( -. 11 Queson 4-6 are based on the following graph

opulaon of !hutan b" #ge$%&1& es'ate(

( s r a e " $

4op!laonMale5tho!sand s6 4op!laon-emale5tho!sa nds6

e g #

opulaon$thousands(

. $pproximately what percent of &h!tan’s total pop!laon was between the ages 0 and 1 years in 2010# $. 1% &. 2% ". 30 ). 0 *. %% %. +hat is the best esmate of the rao of the female pop!laon age 7% and older to the female pop!laon age 0 to 1 years# $. 1810 &. 18% ". 183

). 381 *. %81 7. +hich of the following is greater than %0# Indicate all that apply. $. Males and females ages 01 to total pop!laon. &. Males age01 to males and -emales ages01. ". Males ages 1%7 to total pop!laon. ). Males and -emales ages 01 to males and females ages 1%7. *. Males oer 7% to Males and -emales ages oer 7%.

Quesons )-1& are based on the following graphs Distribuon of students at *had" !roo+ ,igh *hool

.hart / itle

'. /!ppose there were 1100 st!dents at /hady &roo: ;igh /chool in 200% and 1300 st!dents in 2010.;ow many more freshmen ahere were 9(' st!dents in 200% and '%0 st!dents in 2010. ). >here were 1,1%( st!dents in 200% and ('% st!dents in 2010. -. >here were 107 st!dents in 200% and 100 st!dents in 2010.

Inter'ediate Queson 11-13 are based on the following graphs 0u'ber of lanes at *her'an #irport

s e in l r i#

year2010 year2000

0u'ber of lanes

ollisions between !irds and lanes near *her'an #irport

no of ollisions

no of colli sions

0o of ollisions s "ear 11. >he n!mber of collisions between birds and planes near /herman $irport increased by

approximately what percent between 1990 and 2010# $. 3 &. 3' ". 193 ). 2% *. 31'

12. +hat is the probability that a collision between a bird and a plane in 2010 inoled a s!per bl!e plane, ass!ming that collisions between birds and planes inoled only ?mega, /!per &l!e and -ast @et airplanes# $. 11% &. 13 ". %13 ). (11 *. 11% 13. &ased on the data gien in the graph, approximately what percentage of collisions between planes and birds between 1990 and 2010, incl!sie occ!rred before 2002# $. 12 &. 20 ". 33 ). %0 -. 7'

Quesons 14-16 are based on the following graphs

nu'ber of !ear sighngs2statewide

n!mber of &ear sighngs,statewide

/he nu'ber of *ighngs s "ear

/"pial Reasons for !ear *ighngs

petsliestoc:A 10A 10.00

property damageA 1%A 1%.00

&ird feedersA 2%A 2%.00 >rashA 30A 30.00

property damage >rash on Boad &ird feeders petsliestoc:

on BoadA 20A 20.00

1. If /mithson "o!nty reported 20  of the bear sighngs in the state in 2000, how many /ighngs were reported for the locaon# $. 20 &. 2% ". 30 ). 0 *. %0 1%. )!ring the year that had the greatest increase in the n!mber of bear sighngs from the preio!s year, how manyC on roadC sighngs were reported, ass!ming a typical distrib!on of bearsighng types# $. 20 &. 3% ". 0 ). '0 *. (0 17. $ccording to the data gien, in which year was there no change in the n!mber of bear sighngs from the preio!s year#

/elect all that apply $. 2002 &. 2003 ". 200 ). 200% *. 2007

Quesons 1)-%& are based on the following graphs

no ofDDs ordered in%&1&

no of)D)Es ordered in2010

DD5s ordered in 'illions

DD5s ordered in Dee'ber %&1&

childrenA 13A 13.00 horrorA (A (.00 "omedyA 3'A 3'.00

)ramaA 19A 19.00

children horror )rama $con "omedy

$conA 23A 23.00

1'. >here was a 1.7' change in the n!mber of )D)’s ordered between which two consec!e months in 2010# $. -ebMarch &. $prilMay ". May@!ne ). $!g/ept *. Fo)ec 1(. +hich pairs of months in 2010 hae a sales rao of 283# /elect all that apply $. @an 8-eb &. $pril 8May ". $!g!st 8$pril ). ?ctober 8 Foember *. May8 @!ne 19. In )ec2010,how many more comedy )D)’s were ordered than drama )D)s# $. .2 m &. 7.3m

". (m ). 1.m *. 1(m

20. /!ppose 1% of the )D)’s ordered inFoember2010 were horror Glms. ;ow many more horror Glms were ordered in )ecember than Foember# million

#daned Quesons %1-%4 are based on the following graphs erentage of !o"s and Girls in #endane at re'ier 7eague *oer a'p 200'A '% 2010A 7' 200(A %7 2009A %1 2009A 9 200(A  2010A 33 200'A 2%

girls boys

aendane

a