General Syllabus - see Canvas

Skill Set

Edfinity

We will be using Edfinity for this course, integrated with Canvas. To enroll in our Edfinity section, please follow the steps below:

1. Important: Upgrade to the latest version of Google Chrome or Firefox on a Windows/Mac computer. Other browsers like Safari and devices like Chromebooks can cause issues when you access Edfinity via Canvas.
2. If you already have created an account on Edfinity, make sure you are signed out of edfinity.com.
3. Log into Canvas.
4. Click on the Edfinity link in the Canvas navigation menu to launch.
5. You will be prompted to pay (if applicable) and enroll in our course.
6. Start working on your assignments!
        

A pdf of the STAT 3090 lecture guide will be available to you on your cavas course.  It is strongly suggested that you go to the Clemson bookstore to request a hard copy of the lecture guide.

Supplemental Textbook

After completing this course, students will be able to
1. Identify and distinguish between types of variables, and know which types of variables are required for statistical techniques
2. Explain and apply measures of central tendency, spread, and relative standing and how these different measures relate to each other in various distribution patterns
3. Apply rules of probability, and extend those principles to discrete and continuous probability distributions
4. Explain and apply the concept of sampling distributions and their role in developing confidence intervals and use in hypothesis testing, correctly utilizing the Normal, T or Chi Squared distributions
5. Calculate and interpret confidence intervals for the mean, proportion, and the difference between two proportions
6. Identify the correct statistical test to be used for hypothesis testing for mean, difference between two means, proportion, and standard deviation
7. Clearly interpret the results of statistical analysis in context of the original research question
8. Correctly and appropriately use correlation and linear regression techniques, including inference on the models

Edfinity

• Clemson Academic Success Center