This part of the activity is designed to get familiarity with distributions, both in terms of understanding how they differ from one another, as well as being able to recognize the types of data and variables that would be paired with them. Complete the table on this worksheet (attached below) by doing the following:

a. Identify the characteristics of each distribution listed. Include if it is discrete or continuous, any identifying or distinguishing features, and the general parameters that are used to define it (i.e., what input(s) would Crystal Ball (for simulations) need to create it).

b. For each distribution, come up with 2 separate examples of healthcare variables likely to fit the distribution. ((For example, don't just say "medications", but "count of the number of medications taken per day by a patient" - don't use this one as your example.))?

c. For each example you provided in part b, include likely and appropriate parameters for the distribution. In other words, what are the values that would be required for that example to tell Crystal Ball (virtual lab) how to create the distribution?

d. Are there any other probability distributions you know of that might also fit this variable? Why, or when? Sometimes there may be only one that fits well. If so, state that.

A B C DISTRIBUTION D E EXPONENTIAL DISTRIBUTION CHARACTERISTICS HEALTHCARE EXAMPLES F EXAMPLE PARAMETERS 1. POTENTIAL ALTERNATE DISTRIBUTION? WHEN? 2. 2. 2 3 NORMAL 1. 1. 2. 2. 2 POISSON Discrete, 1 . 1 . 12. 2 5 2. + (Student's t) 2. 2 2 6 TRIANGULAR 12. 2. 7 2 UNIFORM 2. 2. 2. 8 UNIFORM (DISCRETE) Discrete. 2. 2. 9 2. YES/NO Discrete