Really? Fourteen? All the way back to 1944? Wow.
I thought it would be interesting to visualize the percentage of female ASA presidents over time. I found a spreadsheet of past ASA presidents online and used the data to create a timeline. (R script shown.)
# download file library(XLConnect) url <- "http://www.amstat.org/about/pdfs/History_of_ASA Presidents-JSMs.xlsx" local <- tempfile() download.file(url, local, mode='wb') wb <- loadWorkbook(local) dat1 <- readWorksheet(wb, sheet=1) # keep first three columns and valid rows dat2 <- dat1[, 1:3] names(dat2) <- c("Year", "Number", "President") dat2$Year <- as.numeric(dat2$Year) dat2 <- dat2[!is.na(dat2$Year), ] # fill in empty rows library(zoo) dat2 <- na.locf(dat2, fromLast=TRUE) # add sex dat2$Sex <- ifelse(dat2$Year %in% c(1944, 1952, 1956, 1980, 1987, 1989, 1992, 1996, 2006, 2007, 2009, 2011, 2013, 2016), "Female", "Male")
Most recent 10 years of ASA presidents.
|2012||107th||Rodriguez, Robert N.||Male|
|2009||104th||Morton, Sally C.||Female|
|2008||103rd||Lachenbruch, Peter A.||Male|
I then calculated the rolling 10-year percentage of ASA presidents that were female and plotted the results.
# 10-year rolling mean mean10 <- 100*rollmean(dat2$Sex=="Female", 10, align="left", fill=NA) # plot timeline # par(mar=c(4, 4, 3, 1), las=1) # plot(dat2$Year, mean10, type="n", xlab="Year", ylab="Females (%)", # main="Rolling 10-Year Percentage of Female ASA Presidents") # abline(h=50, lty=2) # points(dat2$Year, mean10, type="o", pch=16, col="orange")
There were three female ASA presidents between 1944 and 1956, followed by a 23-year period during which all the presidents were male (1957-1979). Since then, the percentage of female ASA presidents has risen, reaching 50% for the first time during the 10-year period from 2004 to 2013. Excellent.