Math Problem Statement

A company producing orange juice buys all its oranges from a large orange orchard. The amount of juice that can be squeezed from each of these oranges is approximately normally distributed with a mean of 4.7 ounces and some unknown standard deviation. The company’s production manager knows that the probability is 30.85% that a randomly selected orange will contain less than 4.5 ounces of juice. Also, the probability is 10.56% that a randomly selected orange will contain more than 5.2 ounces of juice. a) What is the probability that a randomly selected orange will contain between 4.2 and 4.9 ounces of juices? b) What is the probability that a randomly selected orange will contain more than 4.2 ounces of juices?"

Solution

We are given a normally distributed random variable XX representing the amount of juice from an orange, with a mean μ=4.7\mu = 4.7 ounces and an unknown standard deviation σ\sigma. To solve this problem, we will first need to find the standard deviation σ\sigma by using the probabilities and corresponding values provided.

Step 1: Standardization of the normal distribution

The random variable XX follows a normal distribution N(μ=4.7,σ)N(\mu = 4.7, \sigma), so we can transform XX to the standard normal variable ZZ using the formula:

Z=XμσZ = \frac{X - \mu}{\sigma}

We know two probabilities:

  • P(X<4.5)=0.3085P(X < 4.5) = 0.3085
  • P(X>5.2)=0.1056P(X > 5.2) = 0.1056

These probabilities correspond to the cumulative probabilities for standard normal values of ZZ, so we will use the standard normal table (or inverse Z-scores) to find the corresponding Z-values for 4.5 and 5.2 ounces.

Step 2: Finding the Z-scores for the known probabilities

  • From the cumulative standard normal distribution table, the Z-score that corresponds to P(Z<z)=0.3085P(Z < z) = 0.3085 is approximately z=0.5z = -0.5. This gives us: Z=4.54.7σ=0.5Z = \frac{4.5 - 4.7}{\sigma} = -0.5 Solving for σ\sigma: σ=4.54.70.5=0.20.5=0.4\sigma = \frac{4.5 - 4.7}{-0.5} = \frac{-0.2}{-0.5} = 0.4

  • Now, to verify with the second probability P(X>5.2)=0.1056P(X > 5.2) = 0.1056, we first note that P(X>5.2)=1P(X<5.2)P(X > 5.2) = 1 - P(X < 5.2), so: P(X<5.2)=10.1056=0.8944P(X < 5.2) = 1 - 0.1056 = 0.8944 The Z-score corresponding to P(Z<z)=0.8944P(Z < z) = 0.8944 is approximately z=1.25z = 1.25. Now check this with the calculated σ\sigma: Z=5.24.7σ=1.25Z = \frac{5.2 - 4.7}{\sigma} = 1.25 Solving for σ\sigma: σ=5.24.71.25=0.51.25=0.4\sigma = \frac{5.2 - 4.7}{1.25} = \frac{0.5}{1.25} = 0.4

Thus, the standard deviation is σ=0.4\sigma = 0.4.

Step 3: Answering the questions

a) Probability that a randomly selected orange will contain between 4.2 and 4.9 ounces of juice

We want to find P(4.2<X<4.9)P(4.2 < X < 4.9). First, we convert these values to their corresponding Z-scores: Z4.2=4.24.70.4=0.50.4=1.25Z_{4.2} = \frac{4.2 - 4.7}{0.4} = \frac{-0.5}{0.4} = -1.25 Z4.9=4.94.70.4=0.20.4=0.5Z_{4.9} = \frac{4.9 - 4.7}{0.4} = \frac{0.2}{0.4} = 0.5

Now we use the standard normal table to find the probabilities:

  • P(Z<1.25)0.1056P(Z < -1.25) \approx 0.1056
  • P(Z<0.5)0.6915P(Z < 0.5) \approx 0.6915

Thus, the probability that the juice amount is between 4.2 and 4.9 ounces is: P(4.2<X<4.9)=P(Z<0.5)P(Z<1.25)=0.69150.1056=0.5859P(4.2 < X < 4.9) = P(Z < 0.5) - P(Z < -1.25) = 0.6915 - 0.1056 = 0.5859

b) Probability that a randomly selected orange will contain more than 4.2 ounces of juice

We want to find P(X>4.2)P(X > 4.2). This is the complement of P(X<4.2)P(X < 4.2): P(X>4.2)=1P(X<4.2)P(X > 4.2) = 1 - P(X < 4.2)

From earlier, we know P(X<4.2)=P(Z<1.25)0.1056P(X < 4.2) = P(Z < -1.25) \approx 0.1056, so: P(X>4.2)=10.1056=0.8944P(X > 4.2) = 1 - 0.1056 = 0.8944

Final Answers:

  • a) The probability that a randomly selected orange will contain between 4.2 and 4.9 ounces of juice is approximately 0.5859.
  • b) The probability that a randomly selected orange will contain more than 4.2 ounces of juice is approximately 0.8944.

Would you like more details or have any questions? Here are 5 related questions to consider:

  1. How can we use the normal distribution to approximate other types of distributions?
  2. What happens to the probabilities if the standard deviation of juice yield increases?
  3. How would the calculation change if the mean juice yield was different?
  4. Can you find the probability for a different range, such as between 4.5 and 5.5 ounces?
  5. How does the Central Limit Theorem apply to the production of orange juice in this case?

Tip: Remember that cumulative normal distribution tables give the area to the left of a Z-score. Use complements for probabilities to the right.

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Math Problem Analysis

Mathematical Concepts

Normal Distribution
Standard Deviation
Probability

Formulas

Z = (X - μ) / σ
P(X > x) = 1 - P(X < x)

Theorems

Empirical Rule
Z-Score Theorem

Suitable Grade Level

Grades 11-12