Intro Stats Preview

Introductory Statistics for Credit - a 1 week preview

Slides from the video

Aim of Course:

After taking this one-week course, you will be able to 

  • Specify statistically-valid designs for basic studies
  • Calculate metrics of location, variation and distance
  • Deal with data in different formats
  • Explain the use of hypothesis testing in assessing the role of chance
  • Explain statistical signfiicance

This course covers a selection of materials from Statistics 1, and in addition to introducing the above topics is intended as a preview and illustration of how courses operate at  No background, other than some experience with Excel, is necessary. 

Course Program:

WEEK 1:  Study Design, Statistical Significance

  • Intro, Study Design
  • Measures of Central Location and Variability
  • Distance
  • Data Format
  • Variables
  • Graphs
  • Null Hypothesis
  • Resampling
  • Normal Distribution
  • Significance

Homework in this course consists of short answer problems, and includes exercises that require the use of computer software.

This course also has supplemental readings available online and video illustrations.


Intro Stats Preview

Who Should Take This Course:
Those wishing a brief introduction to key statistical concepts, and anyone considering taking a course at who wants to know how our courses operate.
Basic arithmetic, some exposure to Excel, and a willingness to learn new software.
Organization of the Course:

This course takes place online at the Institute for 1 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. Course participants will be given access to a private discussion board. In class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

At the beginning of each week, you receive the relevant material, in addition to answers to exercises from the previous session. During the week, you are expected to go over the course materials, work through exercises, and submit answers. Discussion among participants is encouraged. The instructor will provide answers and comments, and at the end of the week, you will receive individual feedback on your homework answers.

Time Requirement:
About 15 hours per week, at times of  your choosing.

Options for Credit and Recognition:Students come to the Institute for a variety of reasons. As you begin the course, you will be asked to specify your category:
  1. No credit - You may be interested only in learning the material presented, and not be concerned with grades or a record of completion.
  2. Certificate - You may be enrolled in PASS (Programs in Analytics and Statistical Studies) that requires demonstration of proficiency in the subject, in which case your work will be assessed for a grade.
  3. CEUs and/or proof of completion - You may require a "Record of Course Completion," along with professional development credit in the form of Continuing Education Units (CEU's).  For those successfully completing the course,  CEU's and a record of course completion will be issued by The Institute, upon request.
  4. Other options - Specializations, INFORMS CAP recognition, and academic (college) credit are available for some courses
Course Text:
Course materials included - no additional cost.

This is a 1-week course and we have designed it so that you can complete most of this course and answer most of the exercises without using software.  On the other hand, software is an essential part of statistical work, so the use of software is discussed in the readings and exercises.  If you want to use software, here are the details:

We recommend one of these 3 options:

  1. Regular Excel (not Excel Starter) and Box Sampler
  2. Regular Excel (not Excel Starter) and Resampling Stats for Excel
  3. StatCrunch
  4. R

Excel: you will need to have some facility with using formulas in Excel. If you don't, please review either this tutorial or this tutorial before the course starts.

Box Sampler: this is a free add-in for Excel, designed as a visual teaching and learning tool for doing resampling simulations. Runs only on Windows.  Installation file is here, documentation here.

Resampling Stats for Excel: this is a commercial add-in for Excel, designed as a practitioner's tool for doing resampling simulations. A free license is available to all course participants, while they are enrolled in the sequence of introductory statistics courses. Runs only on Windows. Enrolled students will be given access to a free 1-year trial of Resampling Stats through the software download link on the main Stats course webpage.  You can also visit the Resampling Stats website and download the 1-year trial here.

StatCrunch: this is a very affordable web-based statistical software program, which also has simulation and resampling capabilities. Runs over the web, so can be used with both Windows and Mac. Resampling is not as intuitive as with Box Sampler and Resampling Stats for Excel.  Learn more at

NOTE for StatCrunch Users:  On all platforms, we recommend that you use the New version of StatCrunch.  All examples in the textbook supplement are based on the New version of StatCrunch.

R: R is a powerful opensource statistical scripting language that is widely recognized as an industry standard.  You will need to have familiarity with R and RStudio prior to taking the Statistics 1, 2 or 3 courses if you choose to use R as your software package.  Comprehensive supplemental materials are available for R users.  You can learn more about R hereand RStudio here.



March 17, 2017 to March 24, 2017 April 21, 2017 to April 28, 2017 May 19, 2017 to May 26, 2017 June 16, 2017 to June 23, 2017 July 21, 2017 to July 28, 2017 August 18, 2017 to August 25, 2017 September 22, 2017 to September 29, 2017

Intro Stats Preview


March 17, 2017 to March 24, 2017 April 21, 2017 to April 28, 2017 May 19, 2017 to May 26, 2017 June 16, 2017 to June 23, 2017 July 21, 2017 to July 28, 2017 August 18, 2017 to August 25, 2017 September 22, 2017 to September 29, 2017

Course Fee: $99

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First time student or academic? Click here for an introductory offer on select courses. Academic affiliation?  You may be eligible for a discount at checkout.

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