#Get data for fall 2015 PhD statistics admission decisions
one_yr_data = brewdata( years=2014 )
head( one_yr_data )
### Remaining examples commented out to satisfy CRAN policies ###
#Get several years of data
#yrs=2014:2015
#multi_yr_data = brewdata( years=yrs ); head( multi_yr_data )
#results_by_school = split(multi_yr_data[,-1],multi_yr_data$school_name)
#Find 2014 results for Chicago Booth
#f14 = brewdata( years=2014, map=TRUE )
#booth = f14[ grepl( "booth", tolower( f14$original_name ) ), ]
#booth
#Continuing with the f15 & school data, let's analyze results from a particular
#school, e.g. University of Washington
#uw = f15_by_school$'univ washington'; uw #show all UW decisions
#uw_stats = uw[ uw$gre_v!=0 & uw$gre_q!=0, ] #UW decisions with GRE stats
#plot( uw_stats$gpa, uw_stats$gre_q, xlab="Undergrad GPA", ylab="GRE Quant Score",
# main="University of Washington GPA vs GRE Quant", pch=NA )
#col_key = c('darkgreen','gold','red','black','darkgrey')
#lab = factor( uw_stats$decision, levels=c('A','W','R','I','N') )
#text( uw_stats$gpa, uw_stats$gre_q, label=lab, col=col_key[lab], cex=0.85 )
#Plot the last two years of Berkeley's GPA/GRE Quant decision trends
#yrs=2013:2014
#data = brewdata( years=yrs ); head( data )
#berk = split(data[,-1],data$school_name)$'univ california berkeley'
#berk_stats = berk[ berk$gre_v!=0 & berk$gre_q!=0, ]
#plot( berk_stats$gpa, berk_stats$gre_q, xlab="Undergrad GPA", ylab="GRE Quant Score",
# main="Berkeley GPA vs GRE Quant Fall 2010-2015", pch=NA )
#col_key = c('darkgreen','gold','red','black','darkgrey')
#lab = factor( berk_stats$decision, levels=c('A','W','R','I','N') )
#points( jitter( berk_stats$gpa ), jitter( berk_stats$gre_q ),
# col=col_key[lab], pch=20)
#lgd=c("Accepted", "Wait listed", "Rejected", "Interview", "Not Reported" )
#legend( "bottomleft", legend=lgd, col=col_key, pch=20, bty="n", cex=0.75 )
#Plot several years of results of Duke results using the same data from the
#Berkeley download.
#library( scatterplot3d )
#library( rgl )
#duke = split(data[,-1],data$school_name)$'duke univ'
#duke_stats = duke[ duke$gre_v!=0 & duke$gre_q!=0, ]
#col_key = c('darkgreen','gold','red','black','darkgrey')
#lab = factor( duke_stats$decision, levels=c('A','W','R','I','N') )
#scatterplot3d( duke_stats$gpa, duke_stats$gre_q, duke_stats$gre_v,
# xlab="Undergrad GPA", ylab="GRE Quant Score", zlab="GRE Verbal Score",
# main="Duke GPA vs GRE Quant vs GRE Verbal Fall 2010-2015", pch=20,
# color=col_key[lab] )
#plot3d( duke_stats$gpa, duke_stats$gre_q, duke_stats$gre_v,
# xlab="Undergrad GPA", ylab="GRE Quant Score", zlab="GRE Verbal Score",
# main="Duke GPA vs GRE Quant vs GRE Verbal Fall 2010-2015", pch=20,
# col=col_key[lab] )
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