Essential Information:

Instructor: Dr. Julie M. Clark
Office: Dana 107 Office Phone: -6524
Office Hours: 1:30-2:30 Mondays, Tuesdays, Wednesdays, 11:00-12:00 Tuesdays & Thursdays, and by appointment, and by chance.
Course Schedule: MWF, 10:20 – 11:20 AM
Location: DANA 111

Class Schedule
Homework Assignments
Applets and Data Sets
Online Glossary for text

Text: Investigating Statistical Concepts, Applications, and Methods, 3rd Edition, by Beth L. Chance and Allan J. Rossman. Purchase a pdf ($5) or printed edition ($20) here .


Minitab Basics
Frequently asked Minitab Questions
Minitab Help Demos
Minitab Resource Center


Download R Studio
ISCAM Workspace: ISCAM.RData
Entering Data in R

Dr. Clark’s Advice for Success in this Course:
  • Check the Moodle site and your email frequently (daily!) for assignments,  clarifications, typo corrections, hints, friendly reminders, answers to questions, etc.
  • Do your “homework” every day! This means, complete the assigned Investigations and check your knowledge before moving on.  Never fail to submit at least an attempt at a practice problem or to look at my comments on your submissions on practice problems, quizzes and homeworks.
  • Stay on top of the material and continually review.  The concepts and especially the terminology build through the course (starting with the first class!).  You will find week 8 much easier if you remember the material from week 2, for example.  Please do not get even one day behind.
  • Ask questions.  Please give me and your classmates the opportunity to help you, whether it is in class, in my office, via email, or through Moodle.  Ask questions as they come up; don’t wait for the class meetings, or expect someone else to ask.
  • Try to get friendly with the technology early;  it can really be your friend in this course.  Not having access to technology (the applets or Minitab) will NEVER be a suitable justification for not completing an assignment on time.
Academic Conduct:

Hollins sets high standard for academic integrity, and takes academic dishonesty very seriously. The following misconduct is considered an honor offense and is subject to disciplinary action: cheating, plagiarism, knowingly furnishing false information to the college or instructors, and the forgery, alteration or use of college documents or instruments of identification with the intent to defraud. Any student found to be cheating will receive a grade of zero on the assignment or test being taken and may fail the course. She will also immediately be reported to the Honor Court. Collaboration on homework is not seen as cheating and is encouraged.

Some Data Sites:

Data and Story Libary in StatLib (DASL)
U.S. Census Bureau FactFinder
CHANCE Project data sets
Journal of Statistics Education Data Archive
University of Michigan Document Center (Statistical Resources on the Web)
U.S. Data (Crime, Labor, Transportation, Health, Education, Demographics)
Sports Data Surfing
Data Surfing
Real Time statistics
Pew Research Center Datasets
Australia Data and Story Library (OzDASL)
General Social Survey
Data on the Net
StatLib – Datsets Archive
UCLA Statistics Data sets

Other Statistics Links of Interest:

Statistics Every Writer Should Know
Careers in Statistics (ASA)
Careers Involving Probability and/or Statistics
On-Line Statistical Calculations
Statistiscope -a one page univariate stat package created by Mikael Bonnier, Lund, Sweden