Statistics 250 Honors
Introduction to Biostatistics
Spring 2003

Office hours:	By arrangement (or feel free to stop by, though it's best to call ahead to make sure I'll be in)
Course webpage:	http://www.stat.psu.edu/~dhunter/250h
Schedule:	MW 2:30-3:20 in 111 Thomas; F 2:30-3:20 in 011 Sparks
Required Textbook:	Mind on Statistics, by Utts and Heckard
Grading:	The grade for this course will have the following components: Readiness assessment tests (individual) 20% Readiness assessment tests (group) 10% In-class lab reports (pairs) 15% After-class supuplemental lab questions (individual) 5% Final projects (pairs or individual) 20% Final exam (individual) 30%
Makeup work:	If you miss a class day on which there was graded work turned in, you may make it up as long as you explained your absence to me prior to the missed class. Simply sending an email to me beforehand is fine. For labs, you'll be responsible for completing the entire lab (and answering the supplementary questions) on your own. You can email me with questions that might come up as you do the work. For RATs, you'll be allowed to make up the test (see me to schedule a time), and you will receive the same grade on your group RAT that you receive on your individual RAT. These should be made up as quickly as possible, for obvious reasons.
Calculator:	Bring one with you to class. You may use one on tests (and you will often need one). Although you may find a calculator with statistical capabilities helpful, all you need is a calculator that will handle the basic arithmetic operations and square roots.
Policy on academic integrity:	All Penn State and Eberly College of Science policies regarding academic integrity apply to this course. See http://www.science.psu.edu/academic/Integrity/index.html for details.
Course overview:	The things you'll learn this semester fall roughly into one or more of these three areas: Statistical literacy Statistical inference Data analysis Ability to think critically about arguments that use statistics as evidence Drawing conclusions about a population of interest based on a sample from that population Intelligent application of statistical techniques to a dataset, often with the aid of a computer, to answer questions of interest Some of the tools you'll be using: Probability: The science of uncertainty Descriptive statistics: Quantities like mean, standard deviation; graphical techniques Minitab: A statistical software package

If you have any questions, please feel free to contact me. Email is best.