Math Problem Statement

Let z be a standard normal random variable with mean 𝜇 = 0 and standard deviation 𝜎 = 1. Find the value c that satisfies the inequality. (Round your answer to two decimal places.) P(z > c) = 0.0268

Solution

To find the value cc such that P(z>c)=0.0268P(z > c) = 0.0268, where zz is a standard normal random variable (with mean μ=0\mu = 0 and standard deviation σ=1\sigma = 1), we follow these steps:

Step 1: Understand the probability relation

The standard normal distribution is symmetric about 0. We are looking for the value of cc such that the probability of zz being greater than cc equals 0.0268:

P(z>c)=0.0268P(z > c) = 0.0268

This means we need to find cc such that the area to the right of cc under the standard normal curve is 0.0268.

Step 2: Use the cumulative distribution function (CDF)

The cumulative distribution function P(zc)P(z \leq c) gives the probability that zz is less than or equal to a certain value. The relationship between the cumulative probability and the given probability is:

P(z>c)=1P(zc)P(z > c) = 1 - P(z \leq c)

So, we can rewrite the equation as:

1P(zc)=0.02681 - P(z \leq c) = 0.0268

Solving for P(zc)P(z \leq c):

P(zc)=10.0268=0.9732P(z \leq c) = 1 - 0.0268 = 0.9732

Step 3: Find the z-score corresponding to the cumulative probability

Now, we need to find the z-score that corresponds to a cumulative probability of 0.9732. This can be done by looking up the value in the standard normal distribution table or using an inverse cumulative distribution function (also called the percentile function or inverse CDF).

From the standard normal distribution table or using a calculator, the z-score that corresponds to a cumulative probability of 0.9732 is approximately 1.94.

Thus, c=1.94c = 1.94.

Final Answer:

The value of cc that satisfies P(z>c)=0.0268P(z > c) = 0.0268 is approximately 1.94.


Would you like any further explanation or details?

Here are 5 related questions to explore further:

  1. How do you find the z-score corresponding to a given probability without a table?
  2. What is the significance of the standard normal distribution in statistics?
  3. How does the symmetry of the normal distribution affect probability calculations?
  4. Can we use the same method to find the value of cc for P(z<c)=0.0268P(z < c) = 0.0268?
  5. How would the process differ if μ\mu and σ\sigma were not standard values?

Tip: When using z-tables, always remember that they provide the cumulative probability for values less than or equal to a given z-score.

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Math Problem Analysis

Mathematical Concepts

Probability
Statistics
Standard Normal Distribution

Formulas

P(z > c) = 1 - P(z ≤ c)
Cumulative distribution function (CDF)

Theorems

Properties of the Standard Normal Distribution
Inverse Cumulative Distribution Function (Inverse CDF)

Suitable Grade Level

Grades 10-12