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Foundation of Statistics

Next Offering

Start Date: August 22, 2017 
End Date:   October 10, 2017
 

The Foundation of Statistics is one of four non-credit courses in the Certification in Practice of Data Analytics (CPDA) program. The course is taught by faculty from the department of Statistics at The Ohio State University. The course is delivered in 100% distance learning format and includes instructional material equivalent to a one semester credit hour class.   

This course can be taken individually, or as part of the four courses required to receive the CPDA certificate of completion. It is strongly recommended that participants who take the Foundations of Statistics first, followed by Data Mining. Machine Learning or Visualization Analytics and Sensemaking can follow in any order. 
 

Course Description

Foundation of Statistics includes; a short discussion of where data comes from; data exploration; probability and random variables; the basics of statistical inference (e.g., sampling and inferring upon population parameters using statistics); testing statistical hypotheses and building confidence intervals; and an introduction to regression. Students will use the R software package in this course.

4 CEUs are granted upon successful completion of the course.

 

You will learn to:
  1. Describe data graphically and numerically using statistical software.
  2. Explain basic concepts of probability and random variables.
  3. Recognize how data can be used to infer features of probability distributions.
  4. Test for consistency of data with particular values of parameters.
  5. Estimate parameter values and quantify uncertainty in the estimate.
  6. Interpret linear association. 
     
Recommended Prerequisites 

It is strongly recommended that participants have taken at least one course in college level algebra prior to taking this course. Students will be required to learn the R software package prior to starting the course (www.r-project.org).

Free training in R software that will prepare you for this course can be found online at:

https://www.datacamp.com/courses/free-introduction-to-r

or, Free 10 day trail or low cost training also at:

https://www.lynda.com/
Search for "Up and Running with R"

 

Click Here to learn more about how this course is delivered 100% online!

 
Text Book

Participants are required to purchase the following book for this course. 
Introduction to the Practice of Statistics, 7th Edition, Moore, McCabe and Craig (2010). ASIN: 1429274077. Earlier editions of the textbook can be used as well and contain all the same material as the later edition.
 

 

Expected Time Commitment to Complete this Course

Each course is equivalent to a one semester credit hour class. Therefore each class consists of approximately 40 hours of class time that includes 12-13 hours of recorded faculty lectures and 23-24 hours of additional course work. Each course is seven weeks in length, so each week there is 5.7 hours of combined class time (40 hrs / 7 weeks). The average student should allow a 2:1 study-to-class-time ratio to complete the course. This means you should plan to study two hours for each one hour of class time. This equates to 11-12 hours each week to complete all course work. (5.7 hrs X 2 = 11-12 hrs).  Based on a person's own personal strengths and experience, you should increase or decrease the ratio. 
 

Cancellations and Refunds

A full refund minus a $50 administrative fee will be made if cancellation is received three weeks prior to the start of the course. No refunds within three weeks of the course start date. 


Course Offering Dates

Each course offering in this program is faculty lead, therefore it operates with a specific start date and end date. Students must complete each course during the specific time frame. Access to the online course and materials is removed when the course ends.