This course is delivered via videosynchronous class sessions. To be successful, you must actively engage with ideas presented in the course, and with those posed by your classmates.
Assessment is based upon active course participation, weekly assignments, and a culminating course project.
We will use the free statistical computing software R (http://www.rproject.org/) frequently in class. Previous experience with R is required for this course. You will apply what you learned in class to solve your homework and final project problems.
In this class we will learn basic statistical inference procedures of estimation, confidence intervals, and hypothesis testing. We will also cover statistical inference of bivariate data, including correlation and simple linear regression models.
- Confidence intervals for population mean and mean differences
- Confidence interval interpretations
- Hypothesis testing for population mean and mean differences
- Chi-squared hypothesis testing
- P-value interpretations
- Linear regression analysis
- Correlation (hypothesis testing and interpretation)
Synchronous classes offer the opportunity to explore questions about the course and materials beyond the lectures through live interactions—via videoconference—with course faculty and your classmates. Live class sessions will meet weekly.
Course Materials Fee
See full tuition details here.