The results of each analysis will be discussed during the session. You have the option of presenting a 15-minute oral discussion of your results or preparing a poster. Each participant will be given the opportunity to display his/her results and other conference attendees will be encouraged to discuss them with you.

Since this session is treated as an organized contributed-paper session, you must submit a title and abstract to the Society office, chaired by Prof. Friendly. The abstract must be postmarked not later than January 15, 2017. The abstract can be very general. A sample as a model is provided below. Variations might include descriptions of the analyses you carried out, or what you found. You have until the conference to work on the analysis. Please send a (possibly revised) copy of your abstract by email to the conference chair no later than two weeks before the conference. After the meetings you will be given an opportunity to include a short paper describing your analysis in the 2017 Proceedings of the Statistical Education Section of the Hotelling Society.

Sample Abstract

This paper describes and summarizes the relation ships between 1987 salaries of major league baseball players and the player's performance. We use regression methods to show relationships between a player's salary to his 1986 and career performance statistics and the player's team. Some surprising findings are discussed.

Description of the Baseball Data Sets

The data is stored in various formats (SAS input files, SAS stored datasets, SPSS system (.sav) files) on the Hebb server,

• SAS stored datasets are located in the psy6140\lib\ directory;
• SPSS .sav files are in the psy6140\lib\spss\ directory.
• For R, the baseball hitters file is contained in the corrgram package and the vcd package (with slightly different variable names)

  library(corrgram)
  data(baseball)
  

• You can of course read in the CSV files mentioned below directly into R

  baseball <- read.csv("http://friendly.apps01.yorku.ca/psy6140/lib/baseball.csv")
  pitcher <- read.csv("http://friendly.apps01.yorku.ca/psy6140/lib/pitcher.csv")
  team <- read.csv("http://friendly.apps01.yorku.ca/psy6140/lib/team.csv")
  

• Also for R, the Lahman package provides a comprehensive history of baseball statistics from 1871-2015. See the notes below under Other Sources. There is also a baseball-demo.R file that illustrates some basic manipulations of these data sets.

File	SAS input file (raw data)	SAS dataset in psy6140\lib\	View it	SPSS dataset	CSV dataset (comma delimited)
Hitters	baseball.sas	psy614.baseball (V9: baseball.sas7bdat)	hitters.htm	baseball.sav	baseball.csv
Pitchers	basepitc.sas	psy614.pitcher (V9: pitcher.sas7bdat)	pitcher.htm	pitcher.sav	pitcher.csv
Team	baseteam.sas	psy614.team (V9: team.sas7bdat)	teams.htm	team.sav	team.csv
Hitters 921	bball92.sas		bball92.html		bball92.csv
Attendance2	MLBattend.sas				MLBattend.csv
1Contains the Major League baseball players who played at least one game in both the 1991 and 1992 seasons, excluding pitchers, with 1992 salaries.
2Contains home game attendance, wins, losses, etc. for all teams from 1969-2000

Data sources

Note: The data was entered by the Society's clerical staff from coding forms provided by the symposium organizers. While the staff were generally careful and skilled at data entry, and printouts were checked for obvious errors, no checks against original sources were carried out, and the possibility that errors are contained in the data cannot be ruled out. Standard statistical practices of data screening should therefore be included in your analyses.

Goals

If, on examination of the data, you deem some other question(s) of greater interest, feel free to make that the basis of your contribution. In addition you are free to construct other variables from those given (such as batting average, which is calculated as a ratio of the number of hits to times at bat).

Finally, you are also free to gather and use other data related to your chosen question.

• For example, if you are interested in human performance (and physics) you might consider aspects suggested by an analysis of all the things a batter must do in the 400ms it takes a pitch to reach home plate, shown visually in this wonderful image from a paper that Yale physicist Robert Adair gave at the AAAS. (As Adair says, tongue in cheek, hitting a baseball is "clearly impossible." He wrote _The Physics of Baseball_.) But then, you'd have to find some data!
• Or, you might be interested in hitting/winning streaks in baseball, sometimes called the "hot hand" phenomenon. See the hot hand home page for links to this topic (including other sports).

Other sources

• This database is now avalable as the R package, Lahman, containg all the data, and a collection of worked examples.
• lahman58-csv.zip, a ZIP file containing all player statistics from 1871-2010, in a variety of CSV files, with a description in this readme58.txt file.
• Some of the individual files: Batting.csv: batters; Pitching.csv: pitching statistics; Teams.csv: team statistics; Salaries.csv: salary information;
• See this Google Motion Chart of the Teams data, created with the R googleVis package

The Hitter File [baseball.sas]

There is one observation per hitter in the file baseball.sas. Unless otherwise noted, all performance statistics refer to the 1986/87 baseball season. Career statistics count all years that a player actually played in the major leagues (some can get sent back down to the minors and get called up again). The variables are:

NAME	Hitters name
LEAGUE	Player's league
TEAM	Player's team
ATBAT	Times at Bat: Number of official plate appearances by a hitter. It counts as an official at-bat as long as the batter does not walk, sacrifice, get hit by a pitch or reach base due to catcher's interference.
HITS	Hits:
HOMER	Home Runs
RUNS	Runs: The number of runs scored by a player. A run is scored by an offensive player who advances from batter to runner and touches first, second, third and home base in that order without being put out.
RBI	Runs Batted In: A hitter earns a run batted in when he drives in a run via a hit, walk, sacrifice (bunt or fly) fielder's choice, hit- batsman or on an error (when the official scorer rules that the run would have scored anyway).
WALKS	Walks: A ``walk'' (or ``base on balls'') is an award of first base granted to a batter who receives four pitches outside the strike zone.
YEARS	Years in the Major Leagues. As far as we can tell, this counts all years a player has actually played in the Major Leagues, not necessarily consectutive.
ATBATC	Career Times at Bat
HITSC	Career Hits
HOMERC	Career Home Runs
RUNSC	Career Runs Scored
RBIC	Career Runs Batted In
POSITION	Player's position(s). See list of codes used below under Coding for some of the variables. (You are free to recode these as you see fit.)
PUTOUTS	Put Outs. A put out is credited when a fielder causes a batter or runner to be, well, put out; e.g., catches the batter's fly ball, tags a base runner out before he reaches the base, etc.
ASSISTS	Assists. An assist is credited when a fielder assists in a play causing a player to be put out; e.g.,
ERRORS	Errors
SALARY	1987 Annual salary on opening day (in 1000$)
BATAVG	Batting Average, calculated as 1000*(HITS/ATBAT)
BATAVGC	Career Batting Average, calculated as 1000*(HITSC/ATBATC)

The Pitcher File [basepitc.sas]

NAME	Pitcher's name
TEAM	Team at the end of 1986
LEAGUE	League at the end of 1986
WINS	Number of Wins
LOSSES	Number of Losses
ERA	Earned Run Average
GAMES	Number of Games
INNINGS	Number of Innings pitched
SAVES	Number of Saves
YEARS	Years in the major leagues
WINSC	Number of Wins during his career
LOSSESC	Number of Losses during his career
ERAC	Earned Run Average during his career
GAMESC	Number of Games during his career
INNINGC	Number of Innings pitched during his career
SAVESC	Number of Saves during his career
SALARY	1987 annual salary ($1000s)
LEAGUE7	League at the beginning of 1987
TEAM7	Team at the beginning of 1987

The Team File [baseteam.sas]

Coding for some of the Variables

Team Names

   value $team
     'ATL'='Atlanta      '
     'BAL'='Baltimore    '
     'BOS'='Boston       '
     'CAL'='California   '
     'CHA'='Chicago A    '   (Sox)
     'CHN'='Chicago N    '   (Cubs)
     'CIN'='Cincinnati   '
     'CLE'='Cleveland    '
     'DET'='Detroit      '
     'HOU'='Houston      '
     'KC '='Kansas City  '
     'LA '='Los Angeles  '
     'MIL'='Milwaukee    '
     'MIN'='Minnesota    '
     'MON'='Montreal     '
     'NYA'='New York A   '   (Yankees)
     'NYN'='New York N   '   (Mets)
     'OAK'='Oakland      '
     'PHI'='Philadelphia '
     'PIT'='Pittsburgh   '
     'SD '='San Diego    '
     'SEA'='Seattle      '
     'SF '='San Francisco'
     'STL'='St. Louis    '
     'TEX'='Texas        '
     'TOR'='Toronto      '

Leagues

     N    National
     A    American

Divisions

     W    West
     E    East

Player's position(s):

The list below shows the complete set of 2-character codes used for player's position in the baseball.sas hitter's file. These values define a SAS format, $posfmt. which can be used to print the positions in the form shown on the right of the = sign.

   value $posfmt
     '1B' = 'First Base'
     '2B' = 'Second Base'
     'SS' = 'Short Stop'
     '3B' = 'Third Base'
     'RF' = 'Right Field'
     'CF' = 'Center Field'
     'LF' = 'Left Field'
     'C ' = 'Catcher'
     'DH' = 'Designated Hitter'

     'OF' = 'Outfield'
     'UT' = 'Utility'
     'OS' = 'Outfield & Short Stop'
     '3S' = 'Third Base & Short Stop'
     '13' = 'First & Third Base'
     '3O' = 'Third Base & Outfield'
     'O1' = 'Outfield & First Base'
     'S3' = 'Short Stop & Third Base'
     '32' = 'Third & Second Base'
     'DO' = 'Designated Hitter & Outfield'
     'OD' = 'Outfield & Designated Hitter'
     'CD' = 'Catcher & Designated Hitter'
     'CS' = 'Catcher & Short Stop'
     '23' = 'Second & Third Base'
     '1O' = 'First Base and Outfield'
     '2S' = 'Second Base and Short Stop';

   /* Recode position to short list */
   value $pos
     'CS','CD'       ='C '
     'OS','O1','OD'  ='OF'
     'CF','RF','LF'  ='OF'
     '1O','13'       ='1B'
     '2S','23'       ='2B'
     'DO'            ='DH'
     'S3'            ='SS'
     '32','3S','3O'  ='3B' ;

proc means data=psy614.baseball;
   class position;
	format position $pos.;
	var salary;