1. All students know the definition of the notion of independent events, and can use the addition, multiplication, and complementation rules to solve for probabilities of particular events in finite sample spaces.

2. All students know the definition of conditional probability, and use it to solve for probabilities in finite sample spaces.

3. All students demonstrate understanding of the notion of discrete random variables by using them to solve for the probabilities of outcomes, such as the probability of the occurrence of five heads in fourteen coin tosses.

4. All students are familiar with the standard distributions (normal, binomial, and exponential), and can use them to solve for events in problems where the distribution belongs to these families.

5. All students determine the mean and standard deviation of a normally distributed random variable.

6. All students know the definitions of the mean, median, and mode of distribution of real valued data, and can compute them in particular situations.

7. All students compute the variance and standard deviation of a distribution of data.

8. All students organize and describe distributions of data using a number of different methods, including frequency tables, histograms, standard line and bar graphs, stem and leaf displays, scatter plots, and box and whisker plots.

9. All students find the line of best fit to a given distribution of data using least squares regression.