Course description: 
This course is a biomedical engineering specific introduction to statistics, probability, and inference. It is also an introduction to the related skills that are needed to employ statistics, probability, and inference in biomedical engineering contexts. It is primarily concerned with the use of statistical tools for modeling, analysis, and (MOST IMPORTANTLY) making sense of data in biomedical engineering research. The primary focus is practical and applied rather than theoretical but will be theoretical when such understanding is necessary to properly understand the methods covered. Basically, it is an engineering course. Closer to 2110 and 2250 than to whatever flavor of calculus you took.
Concepts list

1.    Types of data and Sampling
2.    Descriptive statistics
3.    Probability and distributions
4.    Bayes theorem and formula
5.    Sensitivity, specificity, and test optimization
6.    Fundamentals of hypothesis testing and degrees of freedom
7.    T-tests
8.    Z-tests
9.    ANOVAs
10.    Non-parametric tests 
11.    Goodness of fit tests
12.    Correlation and Regression
13.    Logistic regression
14.    Sample size, effect sizes, and power
15.    Confidence and prediction intervals