Question

Which one of the followings are true? 1) For discrete random variables X and Y, if the events { X = x } and { Y = y } are independent, the joint probability P( X = x, Y = y) is 0. 2) The number of LCD televisions sold during a day is an example of a continuous random variable. 3) The probability of the success of a trial or observation for a binomial probability distribution depends on the trial or observation that came before it. 4) The probability that the event B occurs under the condition that the event A occurs is called the joint probability of the events A and B. 5) If the random variables X and Y are statistically independent, then their joint probability distribution function equals the product of the marginal probability distribution functions. 6) The expected value of a sum of random variables is equal to the sum of the expected values of each random variable. 7) The mean of a Poisson distribution is always equal to its variance. 8) The probability of a student randomly guessing answers to a true/false exam is best modeled with a binomial distribution. 3,4,5,6 2,4,6,7 1,5,6,8 1,2,5,6 1,2,3,5 1,2,7,8 5,6,7,8 Other:

          Which one of the followings are true?

1) For discrete random variables X and Y, if the events
{ X = x } and { Y = y } are independent, the joint
probability P( X = x, Y = y) is 0.

2) The number of LCD televisions sold during a day is an
example of a continuous random variable.

3) The probability of the success of a trial or observation for a
binomial probability distribution depends on the trial or
observation that came before it.

4) The probability that the event B occurs under the condition
that the event A occurs is called the joint probability of the
events A and B.

5) If the random variables X and Y are statistically
independent, then their joint probability distribution function
equals the product of the marginal probability distribution
functions.

6) The expected value of a sum of random variables is equal to
the sum of the expected values of each random variable.

7) The mean of a Poisson distribution is always equal to its
variance.

8) The probability of a student randomly guessing answers to a
true/false exam is best modeled with a binomial distribution.

3,4,5,6
2,4,6,7
1,5,6,8
1,2,5,6
1,2,3,5
1,2,7,8
5,6,7,8

Other:

Show more…

Which one of the followings are true?

1) For discrete random variables X and Y, if the events
X = x and Y = y are independent, the joint
probability P( X = x, Y = y) is 0.

2) The number of LCD televisions sold during a day is an
example of a continuous random variable.

3) The probability of the success of a trial or observation for a
binomial probability distribution depends on the trial or
observation that came before it.

4) The probability that the event B occurs under the condition
that the event A occurs is called the joint probability of the
events A and B.

5) If the random variables X and Y are statistically
independent, then their joint probability distribution function
equals the product of the marginal probability distribution
functions.

6) The expected value of a sum of random variables is equal to
the sum of the expected values of each random variable.

7) The mean of a Poisson distribution is always equal to its
variance.

8) The probability of a student randomly guessing answers to a
true/false exam is best modeled with a binomial distribution.

3,4,5,6
2,4,6,7
1,5,6,8
1,2,5,6
1,2,3,5
1,2,7,8
5,6,7,8

Other:

Added by Cody Z.

Elementary Statistics a Step by Step Approach

Allan G. Bluman 9th Edition

Instant Answer

Solved by Expert Adi S

05/17/2023

Step 1

For discrete random variables X and Y, if the events X=x and Y=y are independent, the joint probability P(X=x, Y=y) is 0. False. If X and Y are independent, then P(X=x, Y=y) = P(X=x) * P(Y=y). Show more…

Show all steps

lock

Thanks for your feedback!

Which one of the followings are true? 1) For discrete random variables X and Y, if the events { X = x } and { Y = y } are independent, the joint probability P( X = x, Y = y) is 0. 2) The number of LCD televisions sold during a day is an example of a continuous random variable. 3) The probability of the success of a trial or observation for a binomial probability distribution depends on the trial or observation that came before it. 4) The probability that the event B occurs under the condition that the event A occurs is called the joint probability of the events A and B. 5) If the random variables X and Y are statistically independent, then their joint probability distribution function equals the product of the marginal probability distribution functions. 6) The expected value of a sum of random variables is equal to the sum of the expected values of each random variable. 7) The mean of a Poisson distribution is always equal to its variance. 8) The probability of a student randomly guessing answers to a true/false exam is best modeled with a binomial distribution. 3,4,5,6 2,4,6,7 1,5,6,8 1,2,5,6 1,2,3,5 1,2,7,8 5,6,7,8 Other:

Play audio

Feedback

Powered by NumerAI

Adi S and 63 other subject Intro Stats / AP Statistics educators are ready to help you.

Ask a new question

Labs

Want to see this concept in action?

NEW

Explore this concept interactively to see how it behaves as you change inputs.

View Labs

Key Concepts

Recommended Videos

Recommended Textbooks

Transcript

00:01 It is given that we have to examine which of the given statements are true.

00:04 In the first statement, we know that if the random variables x and y are independent, then the joint probability p of x ,x y equal to y would be equal to the marginal probability products of p of x equal to x into p of y equal to y.

00:27 But in the given statement, it is given that p of x equal to x comma y equal to y equal to 0.

00:38 Therefore, the given statement is not the correct statement.

00:41 And in question 2, it is given that the number of lcd television sold is a continuous variable.

00:53 And we know that a continuous variable takes the values from an infinite set.

01:00 But the number of sold are the finite set.

01:04 Therefore, the statement 2 is also not the correct answer.

01:08 And in statement 3, we know that for a binomial distribution, the probability of the success p is fixed.

01:20 But it is given that the probability of the success p depends on a previous, sorry it is given that it is depend on a previous trial.

01:34 Therefore, the statement 3 is also not the correct answer.

01:39 In statement 4, it is given that the probability of the event b under the condition that the event a occurs is represented as a conditional probability.

01:58 But in the given statement, it is given as a joint probability.

02:02 Therefore, the statement 4 is also not the correct answer.

02:06 In statement 5, it is given that the joint density function p of x comma x comma y comma y equal to y would be equal to the product of the marginal probability p of x equal to x into p of y equal to y when they are independent...

Ace is your personal tutor. It breaks down any question with clear steps so you can learn.

Start Using Ace

Continue solving this problem

Create a free account to:

View full step-by-step solution
Ask follow-up questions with Ace AI
Save progress and study later