Prob&Stat Interference Midterm 2

Pataasin ang iyong marka sa homework at exams ngayon gamit ang Quizwiz!

A conditional probability is also known as a posterior probability, which is a revision of the prior probability using additional information.

True

A listing of all the possible outcomes of an experiment for a discrete random variable along with the relative frequency of each outcome is called a discrete probability distribution.

True

A probability is a numerical value that indicates the chance, or likelihood, of a specific event occurring.

True

An expected value is another term for the mean of a probability distribution.

True

At the beginning of a Major League Baseball season, a panel of sports writers decided that the Los Angeles Dodgers were the most likely team to win the World Series that year. This is an example of using subjective probability.

True

Which one of the following is not a valid number for a probability?

1.50

Consider the following events: Event A = The survey respondent is a registered Republican. Event B = The survey respondent lives in Ohio. Events A and B are mutually exclusive.

False

If you are counting the number of customers visiting your store on a given day, you are working with continuous data.

False

Which one of the following statements about probability is not true?

If Events A and B are mutually exclusive, then Event A or Event B must occur. The correct statement is : If Events A and B are mutually exclusive, then both events cannot occur simultaneously. Please refer to the definitions of "mutually exclusive."

The ________ of a discrete probability distribution measures the dispersion of each outcome of the random variable from the mean of the distribution.

Standard Deviation

Which of the following is not a condition of a discrete probability distribution?

The probability of a success must exceed the probability of a failure. This condition only applies to the binomial distribution.

When the discrete random variable is expressed in terms of dollars, the mean of the distribution is known as the _______________.

expected value of the distribution

Two events are considered to be ________ if they cannot occur at the same time during the experiment

mutually exclusive

The data that results from a survey question that uses the Likert Scale is the ________ measurement level.

ordinal

A single die is rolled many times and the side that faces up is recorded. Eventually, we expect the number of times that we observe a 1, 2, 3, 4, 5, and 6 to be relatively close to one another. This expectation is due to the law of large numbers.

True

Because of the ambiguity of the intervals, technically, it's not proper to calculate the mean and standard deviation of ordinal data.

True

Consider the following events: Event A = The survey respondent is less than 40 years old. Event B = The survey respondent is 40 years or older. Events A and B are mutually exclusive and collectively exhaustive.

True

Continuous random variables are outcomes that take on any numerical value in an interval as a result of conducting an experiment.

True

Decision trees are used to display marginal and joint probabilities from a contingency table.

True

Discrete random variables have outcomes that typically take on whole numbers as a result of conducting an experiment.

True

Mathematically, it is impossible for P(A and B) > P(A).

True

The mean and standard deviation for discrete probability distributions are useful when comparing two different distributions.

True

The mean of the binomial distribution represents the long-term average number of successes to expect based on the number of trials conducted.

True

The number of typographical errors found in a manuscript would best be described using a Poisson probability distribution.

True

The probability that Event A or Event B will occur refers to the union of Event A and Event B.

True

The sum of all the probabilities for the simple events in the sample space must be equal to 1.

True

Two events cannot be both independent and mutually exclusive.

True

The Poisson distribution can be used to approximate the binomial distribution when the number of trials is greater than 20 and the probability of success is less than or equal to 0.05.

True -

When the order of objects is important, use permutations

True - Also, when the order of objects is not important, use combinations. Please refer to high school math or ch 6 in the textbook.

When two events are independent, the probability of them both occurring is simply the product of their individual probabilities of occurring.

True - P(A and B)=P(A)*P(B)

The mean of a discrete probability distribution is the weighted average of the outcomes of the random variables that comprise it.

True - mean = SUM(x * P(x) where P(x) is weight (weighted?)

The probability of the union of two events occurring can never be more than the probability of the intersection of two events occurring.

False

The probability that Event A and Event B will occur refers to the union of Event A and Event B.

False

Events A and B are considered to be dependent events if the probability of Event A given the occurrence of Event B is equal to the probability of Event A occurring.

False - A and B are independent events if P(A|B)=P(A)

The probability that a continuous random variable equals a specific value is always equal to 1.0.

False - Always equal to zero. For example, P(X=any specific value) for any continuous variable is 0. Please refer to lecture files.

The probability of a binomial distribution represents the variation that we would see in the number of successes over n trials, assuming the chance of a success is p.

False - Binomial probability refers to the probability of exactly successes on repeated trials in an experiment which has two possible outcomes (commonly called a binomial experiment). So in this statement, you need to replace "the variation" by "probability."

The mean of a discrete probability distribution needs to equal one of the values of the random variables.

False - By definition [mean = SUM(x * P(x)] it is not necessary for mean = x

In a discrete probability distribution, the value of the random variable can fall into more than one of the frequency distribution classes.

False - It can only fall into one particular class. Please refer to definition of mutually exclusive.

The ounces of soda consumed by an adult next month are an example of a discrete random variable

False - The ounces of soda is considered as a continuous variable because you can always break down ounces to a much smaller interval. For example, 1 ounce can range from 1.0000000000 with as many decimal places as possible.

An event represents all of the possible outcomes of an experiment.

False - a sample space represents all of the possible outcomes of an experiment.


Kaugnay na mga set ng pag-aaral

Chapter 21 (G/D Theories), 22 (Developmental Stages), 43 (Musculoskeletal), 44 (Infection), 45 (Peds Meds)

View Set

Hematology in Practice, 2nd edition, Chapter questions

View Set

Unit 3: Chapter 11 Wrap It Up Quiz

View Set

Chapter 28: World War and Revolution

View Set

NEURO - CHAPTER 1 BIOPSYCHOLOGY AS A NEUROSCIENCE: WHAT IS BIOPSYCHOLOGY, ANYWAY?

View Set