Binomial Distribution Review

Which of the following is the correct acronym to describe the appropriate setting for a binomial distribution?

• BITS

• BIMS

• BINS

• BIBS

Binary means...

• There are multiple outcomes available for a scenario

• There are two outcomes for a scenario

• There are three outcomes for a scenario

• There are no outcomes for a scenario.

True or False: Independent means that knowing the outcome of one trial will not impact the results of future trials.

• True

• False

Tags

CCSS.HSS.CP.A.5

True or False: There does not have to be a set number of trials for a binomial setting.

• True

• False

For binomial settings, what does the success probability need to be?

• Any probability that can chance trial to trial

• Any number that is consistent for half of the set number of trials

• A number between 0 and 1 that stays consistent throughout all of the trials

• A number between 0 and 1 that does not need to stay consistent throughout all of the trials

What type of question do we answer using the calculator command:

binompdf(x, p, n)

• P(X = _)

• P(X ≥ _)

• P(X ≤ _)

• P(X ≠ _)

The calculator command binomcdf(x, p, n) only works with which of the following types of questions (in other words, we do not need to adjust it):

• P(X = _)

• P(X ≥ _)

• P(X ≤ _)

• P(X ≠ _)

Tags

CCSS.HSS.ID.A.4

You are doing a question related to the Binomial Distribution and choose to use the calculator command. When our symbol is ≥, the calculator input is...

• 1-binomcdf(n, p, x-1)

• binomcdf(n, p, x-1)

• binomcdf(n, p, x)

• 1-binomcdf(n, p, x)

You are doing a question related to the Binomial Distribution and choose to use the calculator command. When our symbol is <, the calculator input is...

• 1-binomcdf(n, p, x-1)

• binomcdf(n, p, x-1)

• binomcdf(n, p, x)

• 1-binomcdf(n, p, x)

You are doing a question related to the Binomial Distribution and choose to use the calculator command. When our symbol is >, the calculator input is...

• 1-binomcdf(n, p, x-1)

• binomcdf(n, p, x-1)

• binomcdf(n, p, x)

• 1-binomcdf(n, p, x)