Discover a world of knowledge at Westonci.ca, where experts and enthusiasts come together to answer your questions. Get immediate and reliable solutions to your questions from a knowledgeable community of professionals on our platform. Discover detailed answers to your questions from a wide network of experts on our comprehensive Q&A platform.

Which of the following statements is equivalent to [tex]$P (z \geq 1.7)$[/tex]?

A. [tex]$P(z \geq -1.7)$[/tex]

B. [tex][tex]$1 - P(z \geq -1.7)$[/tex][/tex]

C. [tex]$P(z \leq 1.7)$[/tex]

D. [tex]$1 - P(z \geq 1.7)$[/tex]


Sagot :

To determine which statement is equivalent to [tex]\( P(z \geq 1.7) \)[/tex], we need to utilize properties of the cumulative distribution function (CDF) for a standard normal distribution.

1. Understanding [tex]\( P(z \geq x) \)[/tex]:
- For a standard normal distribution, [tex]\( P(z \geq x) \)[/tex] represents the probability that the standard normal variable [tex]\( z \)[/tex] is greater than or equal to a certain value [tex]\( x \)[/tex].

2. Using the Complement Rule:
- The complement of the event [tex]\( z \geq x \)[/tex] is [tex]\( z < x \)[/tex].
- Therefore, [tex]\( P(z \geq x) = 1 - P(z < x) \)[/tex].

3. CDF of Standard Normal Distribution:
- The CDF of a standard normal distribution, [tex]\( \Phi(x) \)[/tex], represents [tex]\( P(z \leq x) \)[/tex].
- Hence, [tex]\( P(z < x) \)[/tex] and [tex]\( P(z \leq x) \)[/tex] are equivalent for continuous distributions.

Given this, we analyze the options:

- Option 1: [tex]\( P(z \geq -1.7) \)[/tex]
- [tex]\( P(z \geq -1.7) \)[/tex] is not equivalent to [tex]\( P(z \geq 1.7) \)[/tex] because the probabilities for [tex]\( z \)[/tex] being greater or equal to 1.7 and -1.7 are different due to the symmetry and properties of the standard normal distribution.

- Option 2: [tex]\( 1 - P(z \geq -1.7) \)[/tex]
- This can be written as [tex]\( 1 - (1 - P(z < -1.7)) = P(z < -1.7) \)[/tex], which is not equivalent to [tex]\( P(z \geq 1.7) \)[/tex].

- Option 3: [tex]\( P(z \leq 1.7) \)[/tex]
- From the properties mentioned above, we know that [tex]\( P(z \leq 1.7) = \Phi(1.7) \)[/tex].
- Since [tex]\( P(z < 1.7) \)[/tex] and [tex]\( \Phi(1.7) \)[/tex] refer to the same probability, it follows that [tex]\( P(z \geq 1.7) = 1 - P(z < 1.7) \)[/tex] which simplifies to [tex]\( 1 - \Phi(1.7) \)[/tex].
- However, due to the symmetry of the distribution, the region from [tex]\( -\infty \)[/tex] to 1.7 (inclusive) encompasses [tex]\( P(z \leq 1.7) \)[/tex], making this selection correct.

- Option 4: [tex]\( 1 - P(z \geq 1.7) \)[/tex]
- This expression simplifies to [tex]\( 1 - (1 - P(z < 1.7)) = P(z < 1.7) \)[/tex]. This is not equivalent to [tex]\( P(z \geq 1.7) \)[/tex]; it's the complement.

Thus, the correct and equivalent statement to [tex]\( P(z \geq 1.7) \)[/tex] among the options is:

Option 3: [tex]\( P(z \leq 1.7) \)[/tex].
Thanks for stopping by. We are committed to providing the best answers for all your questions. See you again soon. Thank you for visiting. Our goal is to provide the most accurate answers for all your informational needs. Come back soon. We're glad you chose Westonci.ca. Revisit us for updated answers from our knowledgeable team.