2.10 Guessing on an exam: In a multiple choice exam, there are 6 questions and 4 choices for each question (a, b, c, d). Nancy has not studied for the exam at all and decides to randomly guess the answers. What is the probability that:

a)

b)

c)

And we can use the complement rule like this:

And replacing we have:

Step-by-step explanation:

Previous concepts

A Bernoulli trial is "a random experiment with exactly two possible outcomes, "success" and "failure", in which the probability of success is the same every time the experiment is conducted". And this experiment is a particular case of the binomial experiment.

The binomial distribution is a "DISCRETE probability distribution that summarizes the probability that a value will take one of two independent values under a given set of parameters. The assumptions for the binomial distribution are that there is only one outcome for each trial, each trial has the same probability of success, and each trial is mutually exclusive, or independent of each other".

The probability mass function for the Binomial distribution is given as:  

Where (nCx) means combinatory and it's given by this formula:  

The complement rule is a theorem that provides a connection between the probability of an event and the probability of the complement of the event. Lat A the event of interest and A' the complement. The rule is defined by:

We can model the number of correct questions answered with a binomial distribution

Solution to the problem

Assuming the following questions:

a) the first question she gets right is the 6th question?  

For this case we want the first 5 questions incorrect and the last one correct, assuming independence we have:

(b) she gets all of the questions right?

For this case we want all the questions right so then we want this:

(c) she gets at least one question right?

For this case we want this probability:

And we can use the complement rule like this:

And replacing we have:

{3 + i, 3 - i, 3, -1}

step-by-step explanation: