## BIO 500 W3 Discussion Question One

*BIO 500 W3 Discussion Question One*

It is time to relate the rules and concepts of probability to the practice of statistics and experimentation. Sampling distributions provide the link between probabilities and data. Recall that the sum of the probabilities of all possible outcomes for a certain event must equal one. Because the variables representing or describing a certain event can take on a range of values, the frequency of each of those values forms a distribution of possible outcomes, each with its own probability of occurrence. View “Central Limit Theorem” (media piece). What is the significance of the frequency histogram illustrated by dice and numbers in “Dice Combination?” How does this relate to the central limit theorem provided in the media? Roll the dice, what were your odds? HINT: Click on Dice Combination in the media.

If you roll the dice, you have to count the total number of two dice. There are two ways to check on your results (Refer to the instructions by clicking Instructions); click on the dice combinations and odds given in the frequency histogram and the table or click the red bar at the right side of the media piece. Explore the basic principle of probability through this media piece. Utilize the quiz to ensure that you understand these basic principles. What is the significance of probability in judgment and decision making in important aspects of health care? Explain your response with an applicable example.

Rolling an ordinary six-sided die is a familiar example of a *random experiment*, an action for which all possible outcomes can be listed, but for which the actual outcome on any given trial of the experiment cannot be predicted with certainty. In such a situation we wish to assign to each outcome, such as rolling a two, a number, called the *probability* of the outcome, that indicates how likely it is that the outcome will occur. Similarly, we would like to assign a probability to any *event*, or collection of outcomes, such as rolling an even number, which indicates how likely it is that the event will occur if the experiment is performed. This section provides a framework for discussing probability problems, using the terms just mentioned.

Since the whole sample space *S* is an event that is certain to occur, the sum of the probabilities of all the outcomes must be the number 1.

In ordinary language probabilities are frequently expressed as percentages. For example, we would say that there is a 70% chance of rain tomorrow, meaning that the probability of rain is 0.70. We will use this practice here, but in all the computational formulas that follow we will use the form 0.70 and not 70%.