Table of Contents
What are the possible values of a random variable if three coins are tossed?
If we toss three coins, we have a total of 2 × 2 × 2 = 8 possible outcomes: HHH, HHT, HTH, HTT, THH, THT, TTH, and TTT, as shown in Figure 6.4 b.
When three coins are tossed then how many number of element are there in the sample space of this event?
The sample space of a sequence of three fair coin flips is all 23 possible sequences of outcomes: {HHH,HHT,HTH,HTT,THH,THT,TTH,TTT}.
What is the probability of getting two heads when 3 coins are tossed?
3/8
Summary: The Probability of getting two heads and one tails in the toss of three coins simultaneously is 3/8 or 0.375.
When three coins are tossed what is the probability of getting one head?
Probability of Tossing Three Coins
| Outcomes | 3 heads | 1 head |
|---|---|---|
| Frequencies | 48 | 100 |
How many coins are tossed in a coin toss?
Four coins are tossed. Let y be the random variable representing the number of tails that occur. What are the values of the random variables? You mean “What values can y take?” The answer is that you can have no tails, four tails and all the whole numbers in between. There is no rocket science here.
What is the probability of each outcome on the coin?
We first note that since the coin is fair, each of the four outcomes HH, HT, TH, TT in the sample space S is equally likely, and so each has a probability of 1/4. (Alternatively, the multiplication principle can be applied to find the probability of each outcome to be 1/2 * 1/2 = 1/4.)
What is the number of tails in the probability distribution?
Let X be the random variable representing the number of tails that occur. What is the probability distribution? There are 2^4 possible results, which is 16 possible results. They are split between the following: 4 tails; 3 tails and a head; 2 tails and 2 heads; 3 heads and a tail; and 4 heads.
How do you construct the probability distribution of a coin flip?
The probability distribution for two flips of a coin was simple enough to construct at once. For more complicated random experiments, it is common to first construct a table of all the outcomes and their probabilities, then use the addition principle to condense that information into the actual probability distribution table.