PLC Statistics Syllabus

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Introductory Statistics introduces students to the major concepts, logic, and issues in statistical reasoning and to the tools involved in collecting, analyzing and drawing conclusions from data. Four broad conceptual themes are explored:

  • Exploring Data: Observing patterns and departures from patterns
  • Planning a Study: Deciding what and how to measure
  • Anticipating Patterns: Producing models using probability and simulation
  • Statistical Inference: Confirming models

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General Numeric Competence: Students are expected to be able to think quantitatively and to have had experience interpreting data displays, graphs, and infographics (e.g., in the news media).

Mathematics: Students must be competent in basic arithmetic and beginning algebra. Traditionally, this course would also require completion of intermediate algebra. But to be more specific (for those students who have not yet taken Algebra II, College Algebra, Intermediate Algebra, or Precalculus), students should be able to:

  • Solve problems and manipulate data involving proportions and percents.
  • Add, subtract, multiply and divide algebraic expressions.
  • Apply the properties of exponents to algebraic expressions.
  • Solve linear equations and inequalities.
  • Factor algebraic expressions.
  • Graph and manipulate linear equations and inequalities in two variables.
  • Create and interpret scientific notation.

Spreadsheets: Students will need to have a basic facility in working with spreadsheet software (e.g., Excel, Calc). Students who do not consider themselves proficient in using spreadsheets to do basic data manipulation should study the basics for using a spreadsheet (e.g., using the online tutorial Spreadsheets with 3.x Calc - chapters 1-3, 7 and 8).

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The focus of this learning content will be on the application of statistics rather than the mathematical underpinnings. Key learner outcomes are:

  • Think statistically.
  • Use spreadsheet tools to manipulate and interpret data.
  • Communicate accurately and comprehensively about data results, conclusions and interpretations.
  • Use a critical framework to evaluate study designs and results.

Structure of Course

Online course

The main content of the course is delivered online via the Open Learning Initiatives (OLI) Statistics course (created by Carnegie Mellon University). We will use the Probability and Statistics version. The free and open version of Probability and Statistics is available for preview and independent learning. Introductory Statistics students must register for the course with OLI, for a fee of $25 USD.

Statistical Software

OLI's Probability and Statistics course includes many hands-on learning activities, termed "Learn by Doing", which include instructions for doing the activity using a number of different statistical software tools.

The following statistics software tools are recommended for use with this course:

  • R, a free software environment for statistical computing and graphics
  • Microsoft Excel, spreadsheet software available for purchase
  • LibreOffice Calc (or OpenOffice Calc), free open source spreadsheet software

If you are interested in programming and/or open source programming projects, you may want to choose to use R (well respected statistical software used by many professionals). Although there is a steep learning curve to programming in R, the Learn by Doing activities provide detailed instructions on what to do. If you use Ubuntu as your operating system, you may want to look into using RLWard, a GUI front end with a console window.

Otherwise, use of spreadsheet software is preferred, either Calc or Excel, because it offers students the opportunity to practice working in a spreadsheet. Knowing how to use a spreadsheet is a broad-based and transferable skill.

Note that the Probability and Statistics course is not specifically designed to use LibreOffice Calc, however all of the Learn by Doing activities may be completed using Calc. Instructions are provided for completing activities, and additional support offered as needed, for students choosing to use Calc.

Other tools available for use, but not recommended:

  • StatCrunch, subscription web access to data analysis data analysis software
  • Minitab, a statistical software program available for purchase
  • Texas Instruments calculator which includes statistical functions (e.g., TI-83 or TI-84)

Course communications

During the course, our main communication tool is a blog. Weekly posts will be used to help students stay on schedule with completing the online coursework and to communicate preparation needs for the subsequent class meeting. All class participants have edit access to the blog and are encouraged to post ideas and links to resources which others might be interested to check out.


Each student should keep a notebook/journal for the course. As it implies, the notebook/journal has a dual role.

  • a place to take notes on the online course content (recommended for content that is new as a way to help you remember it).
  • a place for writing about interesting uses of statistics and any questions, ideas (e.g., for a stats project), or opinions. Each week students will be asked to offer examples of the uses of statistics for discussion at in-person sessions. The journal offers a way for you to demonstrate, document, and enhance your interest and learning about statistics and related areas such as visual presentation of data, use of statistics in the media, history of statistics, application of statistics in particular fields, etc.

In-person meetings

Interested students will meet in person once/week for 1 hour to review the assigned content for the week, as needed, and to extend the concepts learned via group activities, projects, and discussion of statistics in current events.


Students are encouraged to complete two projects:

  • perform exploratory data analysis of an available dataset (late fall to early winter)
  • design and implement a study to test a hypothesis (May-June)

Time Commitment

Including online coursework and 1 hour weekly in-person session:

Point estimate: 6 hrs/wk
95% confidence interval: 5-7 hrs/wk

Caveat: No actual data contributed to the creation of these statistics. These statistics are pure guess work and should be interpreted with extreme caution. Also note that these statistics represent time commitment on average. Actual weekly time invested in learning statistics will vary from one week to another AND for different individuals. However, the teacher sees these estimates as a goal and will be flexible in all aspects of the course in order to accommodate student needs.

Course Schedule

The full course is scheduled to run for 2 semesters, about 32 weeks to complete online coursework and 5 additional weeks to design and run a research study.

The schedule for online course work provides an example of the course organization.