The discrete distribution represented by this p.f. is called the binomion with parameters n and p Thistribution is very important in probability and statistics and will be discussed further in later chapter of this book.
A short table of values of the binomial distribution is given at the end of this book. It can be found from this table, for example, that if X has a binomial distribution with parameters n=10 and p=0.2, then Pr(x=5)=0.0264 and Pr(X 5)=0.0328.
As another example, suppose that a clinical trial is being run. Suppose that the probability that a patient recovers form her symptoms during the trial is p and that the probability is q=1-p that the patient does not recover. Let Y denote the number of patients who recovers out of n independent patients in the trial. Then the distribution of Y is also binomial with parameters n and p. Indeed, whenever an experiment consists of observing n independent trials with only two possible outcomes for each trial, the distribution of the number of trals with a particular one of the outcomes will be binomial with parameters n and p, where p is the probability of the one outcome that we are counting.
The discrete distribution represented by this p.f. is called the binomion with parameters n and p Thistribution is very important in probability and statistics and will be discussed further in later chapter of this book. A short table of values of the binomial distribution is given at the end of this book. It can be found from this table, for example, that if X has a binomial distribution with parameters n=10 and p=0.2, then Pr(x=5)=0.0264 and Pr(X 5)=0.0328.As another example, suppose that a clinical trial is being run. Suppose that the probability that a patient recovers form her symptoms during the trial is p and that the probability is q=1-p that the patient does not recover. Let Y denote the number of patients who recovers out of n independent patients in the trial. Then the distribution of Y is also binomial with parameters n and p. Indeed, whenever an experiment consists of observing n independent trials with only two possible outcomes for each trial, the distribution of the number of trals with a particular one of the outcomes will be binomial with parameters n and p, where p is the probability of the one outcome that we are counting.
การแปล กรุณารอสักครู่..

The discrete distribution represented by this p.f. is called the binomion with parameters n and p Thistribution is very important in probability and statistics and will be discussed further in later chapter of this book.
A short table of values of the binomial distribution is given at the end of this book. It can be found from this table, for example, that if X has a binomial distribution with parameters n=10 and p=0.2, then Pr(x=5)=0.0264 and Pr(X 5)=0.0328.
As another example, suppose that a clinical trial is being run. Suppose that the probability that a patient recovers form her symptoms during the trial is p and that the probability is q=1-p that the patient does not recover. Let Y denote the number of patients who recovers out of n independent patients in the trial. Then the distribution of Y is also binomial with parameters n and p. Indeed, whenever an experiment consists of observing n independent trials with only two possible outcomes for each trial, the distribution of the number of trals with a particular one of the outcomes will be binomial with parameters n and p, where p is the probability of the one outcome that we are counting.
การแปล กรุณารอสักครู่..
