Advanced Statistics and Quantitative Methods

STATS X 402.1
This advanced statistics course emphasizes practical application of statistical analysis. The course covers the role of statistics in the fields of science, economics, nursing, business, and medical research.
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Online
Starting at $865.00
11 weeks
4.0 Credits

About this course:

This advanced course in inferential statistics emphasizes the practical application of statistical analysis. Instruction includes an examination of the role of statistics in research; understanding statistical terminology; use of appropriate statistical techniques; and interpretation of findings in the fields of economics, business, nursing, and medical research. Topics include graphing and tabulation of data; hypothesis testing for small and large samples; chi-squared; statistical quality control; analysis of variance (ANOVA), regression; correlation; and decision making under uncertainty.
Suggested Prerequisites

It is advisable that you complete the following (or equivalent) since they are prerequisites for Advanced Statistics and Quantitative Methods.

Statistics X 402.

Fall 2018 Schedule

These courses are fully online, and there are no in-person classroom meetings.

Available
-
Instructor: Matin Lackpour
363054
Fee:
$865.00
41 days left. Enroll by Sep 24, 2018
See Details
Notes

Coursework must be submitted as Microsoft Word or Excel attachments.

Enrollment limited; early enrollment advised. Enrollment deadline: September 27, 2018. No refund after September 27, 2018. Internet access required. Materials required.

Refund Deadline
No refunds after September 27, 2018
Course Requirements
Internet access required to retrieve course materials.
Book: Statistical Techniques in Business & Economics by Douglas Lind, William Marchal, Samuel Wathen

Contact Us

Our team members are here to help. Hours: Mon-Fri, 8am-5pm

What you will learn.

  • Understand various concepts of statistics and quantitative methods
  • Recognize business, medical, and scientific applications of statistical data
  • Utilize hypothesis testing for small and large samples
  • Understand chi-squared, statistical quality control, regression, and correlation
  • Understand analysis of variance (ANOVA)
  • Understand statistics-based decision making under uncertainty
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