Math Problem Statement

Let X be the number of people who make a pledge during a drive for contributions to a school. Assume there are 500 people contacted in the drive, and each has a probability 0.15 of making a pledge, independent of one another. Estimate P(80 < X).

Solution

The problem provided can be described as follows:

Let XX be the number of people who make a pledge during a drive for contributions to a school. There are 500 people contacted in the drive, and each has a probability of 0.15 of making a pledge, independent of one another. The task is to estimate P(80<X)P(80 < X).

Step 1: Model Selection

Since we are dealing with independent trials (500 people) and each trial has a constant probability of success (0.15), XX, the number of people making pledges, follows a binomial distribution. That is: XBinomial(n=500,p=0.15)X \sim \text{Binomial}(n = 500, p = 0.15) Where:

  • n=500n = 500 is the number of people contacted,
  • p=0.15p = 0.15 is the probability of making a pledge.

Step 2: Approximation with Normal Distribution

For large nn, the binomial distribution can be approximated by a normal distribution using the Central Limit Theorem. The parameters of the approximating normal distribution are: μ=np=500×0.15=75\mu = np = 500 \times 0.15 = 75 σ2=np(1p)=500×0.15×0.85=63.75\sigma^2 = np(1 - p) = 500 \times 0.15 \times 0.85 = 63.75 σ=63.757.98\sigma = \sqrt{63.75} \approx 7.98

Thus, XX can be approximated by N(75,7.982)\mathcal{N}(75, 7.98^2), a normal distribution with mean 75 and standard deviation 7.98.

Step 3: Standardization and Probability Calculation

We are asked to find P(80<X)P(80 < X). To compute this, we standardize the value of 80: Z=80μσ=80757.980.626Z = \frac{80 - \mu}{\sigma} = \frac{80 - 75}{7.98} \approx 0.626

Now, we need to find P(Z>0.626)P(Z > 0.626). Using standard normal distribution tables or a calculator: P(Z>0.626)0.265P(Z > 0.626) \approx 0.265

Final Answer:

P(80<X)0.265P(80 < X) \approx 0.265

Let me know if you would like more details on the steps or calculations.


Here are 5 related questions to expand your understanding:

  1. How would the result change if the probability of pledging was 0.20 instead of 0.15?
  2. Can you explain why the normal approximation works well for large sample sizes in binomial distributions?
  3. How would you calculate the exact binomial probability without using the normal approximation?
  4. What would happen to the probability if we wanted P(X>90)P(X > 90)?
  5. How do we interpret the result of P(80<X)0.265P(80 < X) \approx 0.265 in terms of the school's fundraising campaign?

Tip: For binomial problems with large nn and moderate pp, normal approximations can simplify calculations greatly.

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Math Problem Analysis

Mathematical Concepts

Probability
Binomial Distribution
Normal Approximation
Central Limit Theorem

Formulas

Binomial distribution: X ~ Binomial(n, p)
Normal approximation: Z = (X - μ) / σ
Mean: μ = np
Variance: σ^2 = np(1 - p)
Standard deviation: σ = √(np(1 - p))

Theorems

Central Limit Theorem

Suitable Grade Level

Undergraduate Statistics/Probability