Statistics
Overview
Statistics, the art of making sense out of data and the science of making
decisions in the face of uncertainty, has become a primary tool in a large
majority of the academic and business pursuits of interest to liberal arts
students. Actuarial science, agriculture and fisheries, biology, business,
economics, education, engineering, health and medicine, law, psychology,
political science, quality control, social work, and
sociology/anthropology are among those fields documented to rely heavily
on statistical methodology.
Career opportunities in statistics are abundant and allow a student to
combine an interest in mathematics with an interest in nearly all other
fields. Graduate study is required for most jobs in statistics, and a
concentration in statistics prepares one well for these programs. Over the
past nine years at least 13 students a year have completed a Statistics
Concentration, and many have gone on to complete graduate degrees.
Actuarial science is a career which makes strong use of statistics but is
one which can be entered without graduate study. St. Olaf is a test site
for the Preliminary Actuarial Examinations.
General Education Credit
Statistics courses that fulfill General Education requirements are listed
in the Class and Lab Schedule.
Distribution Credit
Mathematics 112 satisfies one
distribution requirement in Area D. No other statistics course satisfies a
distribution requirement.
Requirements for the Concentration
St. Olaf College offers a concentration in statistics designed to
introduce the field to students who wish to pursue it either as a primary
interest or as a supplement to some other discipline. This concentration
may be earned in conjunction with any major. The student should note
prerequisites for the listed courses.
- Mathematics 262 and 312. (Normally completed by the end of the
junior year.)
- Two additional courses from the categories below, at least one of
which must be from category A (for students with a major in mathematics
both must be from Category A, and must be beyond the minimum number
required for a mathematics major.) Courses within these categories must be
chosen from an appropriate department, and must be approved in advance for
each student by the director of the statistics concentration. Those which
might qualify include the following:
- Courses primarily statistical in nature: Statistics 266, Mathematics 316,
Economics 385, Independent Study,
Independent Research, or Seminar. Seminars in applied
probability/statistics are offere d in the Mathematics Department as
Mathematics 384.
- Courses containing a statistical component: Economics 263 or 374;
Political Science 371; Psychology 231, 236,
237, 250 or 373; Sociology 372.
Credit will not be given for more than one of Statistics 110 and Mathematics 112; credit will not be given for
Statistics 110 or Mathematics 112 following Statistics 263 or Mathematics 312;
credit will not be given for Statistics 263 following
Mathematics 312.
Courses
- Statistics 110 Principles of Statistics
- An introduction to basic concepts in statistics in the spirit of the
liberal arts. Students will learn practical applications, and the language
and reasoning involved in analyzing behavioral and health science data.
Topics include central tendency, dispersion, probability, random
variables, binomial and normal distributions, estimation and hypothesis
testing, contingency tables, analysis of variance, and correlation.
Computer applications are integrated throughout. Not recommended for
students who have successfully completed a term of calculus. Offered both
semesters.
- Mathematics 112 Elementary Statistics
- An introduction to concepts in statistics using a more mathematical
approach than Statistics 110. Topics include
descriptive measures, probability, random variables, binomial and normal
distributions, estimation and hypothesis testing, contingency tables,
analysis of variance, regressions and correlation. Computer applications
using Minitab are integrated throughout. Designed for behavioral and
health science students. Prerequisite: Mathematics Placement
Recommendation. Offered both semesters.
- Mathematics 262 Probability Theory
- "It is remarkable that a science which began with the consideration of
games of chance should have become the most important object of human
knowledge," wrote Laplace in Théorie Analy-tique des
Probabilités. This course combines theory with applications,
covering topics in combinatorial analysis, elementary probability
measures, conditional probability, random variables, special
distributions, mathematical expectations, and limit theorems.
Prerequisite: Mathematics 126 or 128. Offered both semesters.
- Statistics 263 Statistical Problem
Solving
- Statistical Problem Solving gives students the skills necessary to
understand and analyze the data from our information dependent society. We
begin with descriptive statistics, probability, and random variables. We
then study sampling theory, estimation, and classical hypothesis testing.
Finally, we develop a rigorous, practical and theoretical understanding of
simple and multiple regression analysis and use it to solve economics and
business problems. We emphasize the use of real data and realistic
applications using sophisticated programs such as Minitab for Windows.
Written reports are used to link statistical theory and practice to the
communication of problem solving. Prerequisite: Mathematics 119 or 120 or 122.
Offered both semesters.
- Statistics 266 Design of Experiments
- This introduction to the design and analysis of experiments in the
behavioral and health sciences emphasizes the analysis of variance and
related techniques. Computer applications using Minitab, SPSS and/or SAS
are integrated throughout. Prerequisites: Mathematics 262 and 220 or 222, or permission of the instructor.
Spring Semester only
- Statistics 294 Internship
- Statistics 298 Independent Study
- Mathematics 312 Mathematical Statistics
- This 20th-century material has rapidly become a cornerstone of many
disciplines. We will examine sampling distributions, point and interval
estimation, hypothesis testing, analysis of variance, correlation and
regression. Includes computer applications using Minitab. Prerequisite:
Mathematics 262. Offered both semesters.
- Mathematics 316 Linear Models and Data
Analysis
- This course introduces students to statistics as the art of data
analysis via exploratory graphical and numerical methods using current
data sets from a variety of disciplines. Topics will be chosen from
multiple regression/linear model theory, diagnostic analysis and outlier
detection, and log-linear models/logistic regression analysis.
Prerequisite: Mathematics 312. Fall Semester only.
- Economics 385 Introduction to
Econometrics
- Ideal for students interested in sophisticated applications of
mathematical and statistical models in graduate study and/or professional
careers. The course emphasizes theoretical foundations, mathematical
structure, and applications of major econometric techniques including:
ordinary least squares, generalized least squares, dummy variables,
non-linear transformations, instrumental variables, simultaneous equation
modeling (including two and three stage least squares) and time series
models. Students will work on computer-based case projects using extensive
national data series and a sophisticated econometric modeling system. The
course capstone is the development of an econometric model of the national
economy. Prerequisites: Economics 261, and Statistics
263 or Mathematics 312. Fall
Semester only.
- Statistics 394 Internship
- Statistics 398 Independent Research
Faculty
Richard Single (Director)
Assistant Professor of Mathematics,
1995-
Statistics and statistical genetics
Anthony Becker
Associate Professor of Economics, 1987-
Statistics and econometrics
William Carlson
Professor of Economics, 1973-
Statistics and econometrics
Gerald Ericksen
Professor of Psychology, 1963-
Statistics and experimental design
Michael Kahn
Assistant Professor of Mathematics,
1990-95, 1996-
Probability and applied statistics
Richard Kleber
Professor Emeritus of Mathematics,
1960-
Probability and mathematical statistics
Steven Soderlind
Associate Professor of Economics, 1978-81,
1982-
Economics
Theodore Vessey
Professor of Mathematics, 1970-
Stochastic processes