STAB22H3 Chapter 4: Chapter 4

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22 Apr 2011

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Probability - a pattern that emerges clearly only after many repetitions. The proportion of times the outcome will occur in a long series of repetitions. Probability describes only what happens in the long run. (repetitive trials) Random in statistics is a kind of order that emerges in the long run. Random when the individual outcomes are uncertain but there is a regular distribution of outcomes in a large number of repetitions. Probability (random) repetitive trials (look at overall picture) Ex: fair coin = head and tail sides. Simulations useful when a lot trials are down without being practical. Ex: dice, cards, or spinning a roulette wheel, gambling. Probability model description of random phenomenon in the language of mathematics. The sample space (s) of a random phenomenon is the set of all possible outcomes. Each possible outcome is a sample and the sample space contains all possible samples. www. notesolution. com. Ex 4. 6 sample space for tossing a coin four times.

Related Questions

The probability distribution of the random variable X represents the number of hits a baseball player obtained in a game for the 2012 baseball season

x	P(x)
0	0.167
1	0.3289
2	0.2801
3	0.149
4	0.0382
5	0.0368

The probability distribution was used along with statistical software to simulate 25 repetitions of the experiment (25 games). The number of hits was recorded. Approximate the mean and standard deviation of the random variable X based on the simulation. The simulation was repeated by performing 50 repetitions of the experiment. Approximate the mean and standard deviation of the random variable. Compare your results to the theoretical mean and standard deviation. What property is being illustrated?

a.Compute the theoretical mean of the random variable X for the given probability distribution.

Meu = ?

b. Compute the theoretical standard deviation of the random variable X for the given probability distribution.

Sigma =?

c.Approximate the mean of the random variable X based on the simulation for 25 games.

Xbar=?

d. Approximate the standard deviation of the random variable X based on the simulation for 25 games.

S=?

The probability distribution of the random variable X represents the number of hits a baseball player obtained in a game for the 2012 baseball season x P(x) 0 0.167 1 0.3289 2 0.2801 3 0.149 4 0.0382 5 0.0368 The probability distribution was used along with statistical software to simulate 25 repetitions of the experiment (25 games). The number of hits was recorded. Approximate the mean and standard deviation of the random variable X based on the simulation. The simulation was repeated by performing 50 repetitions of the experiment. Approximate the mean and standard deviation of the random variable. Compare your results to the theoretical mean and standard deviation. What property is being illustrated? a.Compute the theoretical mean of the random variable X for the given probability distribution. Meu = ? b. Compute the theoretical standard deviation of the random variable X for the given probability distribution. Sigma =? c.Approximate the mean of the random variable X based on the simulation for 25 games. Xbar=? d. Approximate the standard deviation of the random variable X based on the simulation for 25 games. S=?