STATISTICAL LITERACY and STATISTICAL COMPETENCE in the NEW CENTURY David S. Mre Purdue University THE ENVIRONMENT THE NEW LITERACY THE NEW COMPETENCE THE NEW PROFESSIONALISM
THE ENVIRONMENT The intellectualizing f wrk Need analytical, quantitative, cmputing skills Need interpretive, cmmunicatin skills Multiple jbs, multiple careers Need statistical skills?
THE ENVIRONMENT The demcritizatin f educatin Tertiary educatin is nw replacing secndary educatin as the fcal pint f access t rewarding careers. OECD Educatin at a Glance 2000 University fr the masses Tertiary A % Change entry rate, 1999 1990 1997 Australia 45% +31% Japan 37% na Krea 43% +66% New Zealand 71% +43% United Kingdm 48% +101% United States 45% +8% OECD Educatin at a Glance 2000, 2001
THE ENVIRONMENT Nnstp educatin and training Adults ages 25 64 in frmal jb-related cntinuing educatin: University All adults educated Australia 43% 64% Canada 22% 33% New Zealand 38% 62% United Kingdm 40% 70% United States 35% 47% OECD Educatin at a Glance 2001
THE ENVIRONMENT Tertiary institutins will be challenged nt nly t meet grwing demand thrugh an expansin f places ffered, but als t adapt prgrammes, teaching and learning t match the diverse needs f the new generatin f students. OECD Educatin at a Glance 2001 University educatin nw N lnger a filter brader clientele N lnger esteric link t career Our students are nt us, nly yunger Larger place fr statistics.
U.S. Secndary Schl Graduates Entering Tertiary Educatin Percent 40 45 50 55 60 65 70 1960 1965 1970 1975 1980 1985 1990 1995 2000 Year
WE WANT STATISTICS Elementary Statistics Enrllments Fall 1995: 236,000 students Up 38% frm 1990 Fall 2000: 274,000 students Up anther 16% Advanced Placement Statistics 1997: 7,500 exams 2000: 35,000 exams 1998: 15,500 exams 2001: 43,000 exams 1999: 25,000 exams
THE ENVIRONMENT Wisdm frm research in math educatin Students learn by their wn activities Understanding and prcedures are separate dmains: Drill nly teaches drilling. Mst peple learn frm specific t general: The math mdel desn t wrk. We can t teach a wide audience what we used t think we cvered.
THE ENVIRONMENT A changing discipline Technlgy Back t data, back t science Interdisciplinary emphasis Technlgy Drives changes in the discipline Drives demand fr quantitative skills New cntent emphases New learning tls: The next big change? The infrmatin fld
This Is a Revlutin Smething mmentus is happening, smething far mre cnsequential than a mere technlgical innvatin. The last time we experienced such an innvatin was the inventin f the printing press almst half a millennium ag. Gertrude Himmelfarb
THE NEW STATISTICAL LITERACY Data beat anecdtes Pwer lines and childhd leukemia Will ur children be better ff?...and intuitin General Electric appliance delivery...and even experts Fr every Ph.D., there is an equal and ppsite Ph.D.
THE NEW STATISTICAL LITERACY Think bradly: Is this the right questin? Wh is unemplyed? Think bradly: Des the answer make sense? Only 15% f new entrants int the wrk frce will be native white males. Cmmunicatin: Can yu read a graph? France in a ppulatin pyramid
THE NEW STATISTICAL LITERACY Only big ideas need apply (details autmated). One cluster: The mnipresence f variatin Cnclusins are uncertain Avid inference frm shrt-run irregularity Avid inference frm cincidence The rule fr staying alive as a frecaster is t give a number r give a date, but never give bth at nce. Jane Bryant Quinn
THE NEW STATISTICAL LITERACY Big ideas: Anther cluster: Beware the lurking variable Assciatin is nt causatin Where did the data cme frm? Observatin versus experiment Filters fr nnsense: Triage n the infrmatin fld The Bible Cde predicts the future? It s easy t lie with statistics. But it is easier t lie withut them. Frederick Msteller
THE NEW STATISTICAL COMPETENCE Use autmated tls gracefully What can t be autmated? Keep thinking bradly Statistical thinking (ASA/MAA) The need fr data The imprtance f data prductin The mnipresence f variability and...
Use Autmated Tls Gracefully: An Example Cunt 0 5 10 15 20 25 30 0 2 4 6 8 10 12 Grade pint average Grade pint average 2 4 6 8 10 Grade pint average 2 4 6 8 10-3 -2-1 0 1 2 3 z-scre 0 5 10 15 Grade pint average
THE NEW STATISTICAL COMPETENCE The quantificatin and explanatin f variability Randmness and distributins Patterns and deviatins (fit and residual) Mathematical mdels fr patterns Mdel-data dialg (diagnstics) This is serius stuff Understanding chance variatin One pass thrugh sftware isn t enugh Mdels as interpretive tls Strategies, nt just methds
THE NEW STATISTICAL COMPETENCE Data strategies: an example PLOT YOUR DATA INTERPRET WHAT YOU SEE NUMERICAL SUMMARY? MATHEMATICAL MODEL? But yu can chse the details t fit yur cntext
CHALLENGES Our teaching is t narrw. In the past, quantitative literacy and what yu learn in mathematics classes were seen as largely disjint. Nw, hwever, they shuld be thught f as largely verlapping. Alan Schenfeld Is quantitative literacy ur turf? If the rcket ges up, I dn t care where it cmes dwn. Des statistics retain a cre?