In an experiment, there are n independent trials. For each trial, there are three outcomes, A, B, and C. For each trial, the probability of outcome A is 0.80; the probability of outcome B is 0.10; and the probability of outcome C is 0.10. Suppose there are 10 trials. (a) Can we use the binomial experiment model to determine the probability of four outcomes of type A, five of type B, and one of type C? Explain. a) Yes. Each outcome has a probability of success and failure. b) No. A binomial probability model applies to only two outcomes per trial.     c) Yes. A binomial probability model applies to three outcomes per trial. d) No. A binomial probability model applies to only one outcome per trial. (b) Can we use the binomial experiment model to determine the probability of four outcomes of type A and six outcomes that are not of type A? Explain. a) Yes. Assign outcome B to "success" and outcomes A and C to "failure." b) No. A binomial probability model applies to only two outcomes per trial.     c) Yes. Assign outcome C to "success" and outcomes A and B to "failure." d) Yes. Assign outcome A to "success" and outcomes B and C to "failure." What is the probability of success on each trial?

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Contingency Table

A contingency table can be defined as the visual representation of the relationship between two or more categorical variables that can be evaluated and registered. It is a categorical version of the scatterplot, which is used to investigate the linear relationship between two variables. A contingency table is indeed a type of frequency distribution table that displays two variables at the same time.

Binomial Distribution

Binomial is an algebraic expression of the sum or the difference of two terms. Before knowing about binomial distribution, we must know about the binomial theorem.