If the question is about 4 successful outcomes out of 16 trials, when the probability of success in any single trial is 0.20 and independent of the outcomes of other trials, then the answer is, yes, the binomial experiment can be used.
No. There are many other distributions, including discrete ones, that are symmetrical.
Yes, it is possible for two dependent events to have the same probability of occurring. The probability of an event is dependent on the outcomes of other events, and it is influenced by the relationship between these events. So, it is conceivable for two dependent events to have equal probabilities.
You multiply each term of one binomial by each term of the other binomial. In fact, this works for multiplying any polynomials: multiply each term of one polynomial by each term of the other one. Then add all the terms together.
The expression does not have any real binomial factors. x is a monomial factor, and the other two involve complex numbers.
No, the outcomes of a binomial experiment are considered independent if the probability of success remains the same for each trial and the trials are performed under the same conditions. Each trial's outcome does not influence the outcome of subsequent trials.
If the question is about 4 successful outcomes out of 16 trials, when the probability of success in any single trial is 0.20 and independent of the outcomes of other trials, then the answer is, yes, the binomial experiment can be used.
It is used when repeated trials are carried out , in which there are only two outcomes (success and failure) and the probability of success is a constant and is independent of the outcomes in other trials.
A binomial experiment is a probability experiment that satisfies the following four requirements:1. Each trial can have only two outcomes or outcomes that can be reduced to two outcomes. These outcomes can be considered as either success or failure.2. There must be a fixed number of trials.3. The outcomes of each trial must be independent of each other.4. The probability of a success must remain the same for each trial.
The assumptions of the binomial distribution are that there are a fixed number of independent trials, each trial has two possible outcomes (success or failure), the probability of success is constant across all trials, and the outcomes of each trial are independent of each other.
No. There are many other distributions, including discrete ones, that are symmetrical.
Yes, it is possible for two dependent events to have the same probability of occurring. The probability of an event is dependent on the outcomes of other events, and it is influenced by the relationship between these events. So, it is conceivable for two dependent events to have equal probabilities.
Strictly speaking, there are no cons because they are defined for discrete variables only. The only con that I could think of is the difficulty evaluating the moments and other probabilities for some discrete distributions such as the negative binomial.
Binomial Nomenclature. In other words, using an organisms Genus and Species to classify them into categories.
For an experiment to be classified as a binomial distrbution four critiria have to be met:There must be a fixed number of trials which is denoted by n.Each trial only has two possible outcomes. One is labeled success and the other is failure.the probably of success is p. The probably of failure is 1-pFinally, the trials must be independent of one other (the outcome of one trial does not affect the outcomes of any other trial.)An example of a binomial experiement is flipping a coin.You can set a fixed number of trials. In this case, flipping a coin 3 times.You label head as success and tails as failure.The probability of heads is p=0.5; the probability of tails is 1-p = 1-0.5 = 0.5.Getting heads on the first flip, doesn't change the probability of flipping heads again on the second. Thus the trials are independent.
You multiply each term of one binomial by each term of the other binomial. In fact, this works for multiplying any polynomials: multiply each term of one polynomial by each term of the other one. Then add all the terms together.
The truth is that alot of things come into play, how good of a swimmer are you, how is the weather, are you familiar with the lake and a host of other things but because this is kind of a binomial distribution of probability that means it has two outcomes, you drowned or you do not. So the chance is, statistically speaking, 50-50