53.141.29: Introduction to Statistics, Distance Education Course

Description
This course provides an introduction to descriptive and inferential statistics.  It is designed to fulfill a general education requirement for current college students working towards a graduate or undergraduate degree.  However, this course is open to both degree and non-degree students.  Non-traditional students or professionals who would like to learn some basic quantitative analysis techniques would also benefit from taking this course. Topics covered include numerical and graphical summary procedures, basic probability concepts, discrete and continuous random variables, the Central Limit Theorem, confidence intervals, and hypothesis tests. A complete list of topics is given in the syllabus below.

The course will be taught via distance education with the instructor utilizing Wimba and BlackBoard software packages.  Students will need to have a high speed Internet connection, the ability to use an Internet browser, and either a headset with a microphone, or speakers and a microphone.  There is a required textbook and notebook.  Both will be available in our university bookstore.  In addition, students will be required to purchase and use the statistical software Minitab.  Instructions for download and installation will be provided during the first class.

Links
Syllabus
FAQ sheet
Course details
e-academy eStore (electronic purchase of Minitab)
Minitab macros
Minitab macros: descriptions, usage, and examples
Shared Classroom:
Link: http://passhe2.horizonwimba.com/launcher.cgi?room=_passhe_s__21851_1_842933
Student ID: 16134954
Phone number (if necessary): (646) 367-1174

In preparation for the first class, review summation notation: tex:\quad\sum\limits_{i=1}^n x_i

We will cover a lot of material during the first class, Wednesday evening. We will probably finish Chapters 1 and 2. We may even start to learn about summary statistics, measures of central tendency and variability, for example, the mean (tex:\bar x), the median (tex:\tilde x), and the standard deviation (tex:s).

Course Log

July 2