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4. Let [tex]\( x \)[/tex] equal the number of students out of a random sample of [tex]\( n = 15 \)[/tex] who would like to visit the beach. Let [tex]\( P = 0.6 \)[/tex] be the proportion of students who would like to visit the beach.

i. Give the values of the mean, variance, and standard deviation of [tex]\( x \)[/tex].

ii. Find:
(a) [tex]\( P(x = 7) \)[/tex]
(b) [tex]\( P(x \geq 10) \)[/tex]
(c) [tex]\( P(x = 0) \)[/tex]

Sagot :

Sure, let's go through the solution step-by-step:

Given:
- [tex]\( n = 15 \)[/tex] (sample size)
- [tex]\( P = 0.6 \)[/tex] (proportion of students who like to visit the beach)

Here, [tex]\( x \)[/tex] follows a binomial distribution, [tex]\( x \sim \text{Binomial}(n=15, P=0.6) \)[/tex].

### Part (i): Mean, Variance, and Standard Deviation

1. Mean of [tex]\( x \)[/tex]:
[tex]\[ \text{Mean} = \mu = n \times P = 15 \times 0.6 = 9.0 \][/tex]

2. Variance of [tex]\( x \)[/tex]:
[tex]\[ \text{Variance} = \sigma^2 = n \times P \times (1 - P) = 15 \times 0.6 \times 0.4 = 3.6 \][/tex]

3. Standard Deviation of [tex]\( x \)[/tex]:
[tex]\[ \text{Standard Deviation} = \sigma = \sqrt{\sigma^2} = \sqrt{3.6} \approx 1.8973665961010275 \][/tex]

### Part (ii): Probability Calculations

1. (a) Probability [tex]\( P(x = 7) \)[/tex]:
[tex]\[ P(x = 7) \approx 0.11805577445376002 \][/tex]

2. (b) Probability [tex]\( P(x \geq 10) \)[/tex]:
[tex]\[ P(x \geq 10) \approx 0.40321555041484797 \][/tex]

3. (c) Probability [tex]\( P(x = 0) \)[/tex]:
[tex]\[ P(x = 0) \approx 1.0737418240000026 \times 10^{-6} \][/tex]

### Summary of Results
- Mean ([tex]\(\mu\)[/tex]): [tex]\( 9.0 \)[/tex]
- Variance ([tex]\(\sigma^2\)[/tex]): [tex]\( 3.6 \)[/tex]
- Standard Deviation ([tex]\(\sigma\)[/tex]): [tex]\( \approx 1.8973665961010275 \)[/tex]

For the probability calculations:
- [tex]\( P(x = 7) \approx 0.11805577445376002 \)[/tex]
- [tex]\( P(x \geq 10) \approx 0.40321555041484797 \)[/tex]
- [tex]\( P(x = 0) \approx 1.0737418240000026 \times 10^{-6} \)[/tex]

These steps and results provide a comprehensive breakdown of the problem's solution.