1. 


The sample space of an experiment is the set of all possible outcomes of that experiment. 
2. 


An event need not be a subset of the sample space. 
3. 


Estimated probability is not relative frequency. 
4. 


Estimated probability is an approximation of theoretical probablity. 
5. 


Theoretical probability is an approximation of probability. 
6. 


Estimated probability and theoretical probability are both examples of probability distributions. 
7. 


If E is the event that it will rain today and F is the event that it will not rain today, then E F = S. 
8. 


If E and F are independent events, then P(EF) = P(E) + P(F)  P(E)P(F). 
9. 


If E and F are two independent events, then the sum of P(E) and P(F) cannot exceed 1. 
10. 


There are some events whose probability exceeds 1. 
11. 


There is a one in six chance of rolling a pair of 7s if two dice are rolled. 
12. 


There is a one in six chance of rolling a pair if two dice are rolled. 
13. 


If two events are mutually exclusive, then the sum of their probabilities is 1. 
14. 


If two events are independent, then they are automatically mutually exclusive. 
15. 


If P(EF) = P(E) + P(F), then E and F must be disjoint. 
16. 


There is a 50% chance of rain today and a 50% chance of rain tomorrow. Therefore, there is a 100% chance of rain either today or tomorrow. 
17. 


There is a 50% chance of rain today and a 50% chance of rain tomorrow. Therefore, there is a 75% chance of rain either today or tomorrow. 
18. 


There is a 50% chance of rain today and a 50% chance of rain tomorrow. Therefore, there is a 25% chance that it will rain today but not tomorrow. 
19. 


There is a 50% chance of rain today and a 50% chance of rain tomorrow. Therefore, there is a 50% chance of rain on exactly one of the next two days. 
20. 


If E is the event that an athlete tests positive in a drug test and F is the event that an athlete has used drugs, then P(EF) is the probability that an athlete who has used drugs tests positive. 