1. 


A random variable can assign a different number to each possible outcome. 
2. 


A random variable must assign a different number to each possible outcome. 
3. 


The sum of all the probabilities P(X=x) for all possible values of x must equal 1. 
4. 


The histogram of X will be highest at the expected value of X. 
5. 


The expected value of X is halfway between the largest and smallest possible values of X. 
6. 


The sample means approach the population mean as the sample size gets larger and larger. 
7. 


If is the expected value of X, then the expected value of X = 0. 
8. 


If is the expected value of X, and x_{1}, x_{2}, . . ., x_{n} is a sample of values of X, then (x_{1} + x_{2} + . . . + x_{n}) / n = . 
9. 


If is the expected value of X, and x_{1}, x_{2}, . . ., x_{n} is a sample of values of X, then (x_{1} + x_{2} + . . . + x_{n})/n should be close to if n is large. 
10. 


If a coin is tossed five times, then the probability of heads coming up twice is the same as the probability of heads coming up three times. 
11. 


If heads has come up six times in a row, then tails is more likely to come up on the seventh toss. 
12. 


I If you toss a coin seven times, is more likely that heads will come up six times and tails once than that heads will come up seven times in a row. 
13. 


In a sequence of n independent Bernoulli trials, with a probability p of success in each, we expect to get about np successes. 
14. 


We should expect the actual values of X obtained in experiments to be within one standard deviation away from the mean. 
15. 


If is the expected value of X, and X has a symmetric, bellshaped distrtibution, then Chebyschev's rule does not apply. 
16. 


If is the expected value of X and is the standard deviation, we should expect the average of (X )^{2} to be ^{2}. 
17. 


For any X, approximately 68% of its values obtained in a sample will lie within one standard deviation of its mean. 
18. 


For a normal X, approximately 68% of its values obtained in a sample will lie within one standard deviation of its mean.. 
19. 


For any X, at least 3/4 of its values obtained in experiments will lie within 2 standard deviations of its mean. 
20. 


For a normal X, at least 95% of its values obtained in experiments will lie within 2 standard deviations of its mean. 
21. 


For any X, at least 88% of its values obtained in experiments will lie within 3 standard deviations of its mean. 
22. 


For a symmetric and bellshpaed distribution X, we expect at least 99% of its values obtained in experiments to lie within 3 standard deviations of its mean. 
23. 


A binomial distribution has exactly the same probabilities as a normal distribution. 