# Statistics Cohort: Learning Outcomes and Existing OER

Learning Outcomes

These learning outcomes are the course level outcomes, over the whole course. We will still need to develop outcomes in each chapter of the resource we create. After looking over what was provided by members of our cohort, here is a list of outcomes that I believe we can go with. I did my best to compile everyone’s objectives they provided into a single list. If there is any overlap, or things I left out, we can cut down or add where needed.

1. Explain and apply principles of study design and data collection.
2. Give examples of biased and random sampling techniques.
3. Construct and interpret graphical summaries of data.
4. Identify characteristics of graphs that are poor practice and may mislead an audience.
5. Compute and interpret numerical summary statistics, including central tendency and variability.
6. Construct and draw inferences from charts, tables, and graphs that summarize data from real-world graphically.
7. Analyze study design to rate the reliability of an inference.
8. Compute probabilities of events using probability and counting rules.
9. Apply the concept of a random variable to generate and interpret probability distribution including binomial, uniform, normal, and chi-square.
10. Use the Central Limit Theorem.
11. Determine point estimates, confidence intervals, and appropriate sample size.
12. Perform hypothesis testing and recommend whether the null should be rejected or not.
13. Graphically and numerically describe the relationship between two quantitative variables, including correlation coefficients, coefficients of determination, and regression formulas.

Existing OER

Starting with an existing OER resource, and putting it into Pressbooks, I believe is the most favorable option. We can always add to that resource to build our own, and I would like us to consider doing that – to make this our own resource! Below is a list of what was provided by members of our cohort. We need to settle on which of these resources we would like to start with as our base to adapt.

1. Introductory Statistics by Barbara Illowsky and Susan Dean: OpenStax
2. Ethical Statistics: OpenPSYC
3. https://ecampusontario.pressbooks.pub/introstats/
4. https://ecampusontario.pressbooks.pub/significantstats/

Tchavdar provided the following additional OER resources that have latex source:

https://aimath.org/textbooks/approved-textbooks/vu-harrington/

Does anyone feel strongly about one of the resources shared to use it as our base textbook to start? We can always add to the content with the other material found.