Which BEST describes the difference between a uniform and non-uniform probability model?
Responses
A A uniform probability model has outcomes that all have the same chance of occurring. Whereas, a non-uniform probability model has outcomes that do not all have the same chance of occurring.A uniform probability model has outcomes that all have the same chance of occurring. Whereas, a non-uniform probability model has outcomes that do not all have the same chance of occurring.
B A non- uniform probability model has outcomes that are known. Whereas, a uniform probability model has outcomes that are not known.A non- uniform probability model has outcomes that are known. Whereas, a uniform probability model has outcomes that are not known.
C A uniform probability model has outcomes that are known. Whereas, a non-uniform probability model has outcomes that are not known.A uniform probability model has outcomes that are known. Whereas, a non-uniform probability model has outcomes that are not known.
D A non-uniform probability model has outcomes that all have the same chance of occurring. Whereas, a uniform probability model has outcomes that do not all have the same chance of occurring.
A) A uniform probability model has outcomes that all have the same chance of occurring. Whereas, a non-uniform probability model has outcomes that do not all have the same chance of occurring.
The correct answer is A: A uniform probability model has outcomes that all have the same chance of occurring. Whereas, a non-uniform probability model has outcomes that do not all have the same chance of occurring.
The correct answer is A.
A uniform probability model has outcomes that all have the same chance of occurring. In other words, each outcome has an equal probability of happening. For example, if you roll a fair six-sided die, each side (outcome) has a 1/6 chance of occurring.
On the other hand, a non-uniform probability model has outcomes that do not all have the same chance of occurring. In this case, the probabilities assigned to each outcome are not equal. For example, if you have a bag of colored marbles with different numbers of each color, the chances of drawing each color would not be the same.
To determine the probability distribution of a given model, you need to know the probabilities or relative frequencies associated with each possible outcome. In a uniform probability model, you divide 1 by the number of possible outcomes to get the probability of each outcome. In a non-uniform probability model, the probabilities are specified directly or determined based on data or other information.