QUESTION 7 For a continuous random variable x, the height of the function at x is a. the probability at a given value of x. b. 0.50, since it is the middle value. c. a value less than zero. O d. named the probability density function f(x).

MATLAB: An Introduction with Applications
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Author:Amos Gilat
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Chapter1: Starting With Matlab
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**Question 7**

For a continuous random variable \( x \), the height of the function at \( x \) is:

- a. the probability at a given value of \( x \).
- b. 0.50, since it is the middle value.
- c. a value less than zero.
- d. named the probability density function \( f(x) \).

**Question 8**

For any continuous random variable, the probability that the random variable:

- a. is any number between zero and one.
- b. is more than one, since it is continuous.

*Questions 7 and 8 are related to understanding continuous random variables and their probability density functions (PDF). The correct answer for Question 7 is d, which identifies that the height of the function at \( x \) in a continuous probability distribution is called the probability density function \( f(x) \). Question 8 relates to the properties of probabilities in continuous distributions.*
Transcribed Image Text:**Question 7** For a continuous random variable \( x \), the height of the function at \( x \) is: - a. the probability at a given value of \( x \). - b. 0.50, since it is the middle value. - c. a value less than zero. - d. named the probability density function \( f(x) \). **Question 8** For any continuous random variable, the probability that the random variable: - a. is any number between zero and one. - b. is more than one, since it is continuous. *Questions 7 and 8 are related to understanding continuous random variables and their probability density functions (PDF). The correct answer for Question 7 is d, which identifies that the height of the function at \( x \) in a continuous probability distribution is called the probability density function \( f(x) \). Question 8 relates to the properties of probabilities in continuous distributions.*
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