Find the mean, variance, and standard deviation of the binomial distribution with the given values of n and p. n= 50, p 0.3 %3D

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### Calculating the Mean, Variance, and Standard Deviation of a Binomial Distribution

In this exercise, you will find the mean, variance, and standard deviation of the binomial distribution with the given values of \( n \) and \( p \).

The parameters provided are:
- \( n = 50 \)
- \( p = 0.3 \)

#### Mean
The mean (μ) of a binomial distribution is calculated using the formula:
\[ \mu = n \cdot p \]

For this example:
\[ \mu = 50 \cdot 0.3 \]
\[ \mu = 15 \]

(Note: The value should be rounded to the nearest tenth if necessary.)

#### Variance
The variance (σ²) of a binomial distribution is calculated using the formula:
\[ \sigma^2 = n \cdot p \cdot (1 - p) \]

Plugging in the values:
\[ \sigma^2 = 50 \cdot 0.3 \cdot (1 - 0.3) \]
\[ \sigma^2 = 50 \cdot 0.3 \cdot 0.7 \]
\[ \sigma^2 = 10.5 \]

#### Standard Deviation
The standard deviation (σ) is the square root of the variance:
\[ \sigma = \sqrt{n \cdot p \cdot (1 - p)} \]

Using the calculated variance:
\[ \sigma = \sqrt{10.5} \]
\[ \sigma \approx 3.24 \]

#### Input Instructions
Enter your answer in the answer box and then click "Check Answer".

### Example Screen Layout
- **Remaining Parts**: 2 parts remaining shown in a progress bar.
- **Action Buttons**: Clear All and Check Answer.
  
The example screen captures a typical educational website layout where students input their calculated answers based on provided formulas. Ensure the values are rounded as specified in the instructions.

---

This content guides students through the statistical concepts and computational steps necessary to characterize a binomial distribution's behavior. Understanding these basics are crucial for interpreting and analyzing binomial data effectively.
Transcribed Image Text:### Calculating the Mean, Variance, and Standard Deviation of a Binomial Distribution In this exercise, you will find the mean, variance, and standard deviation of the binomial distribution with the given values of \( n \) and \( p \). The parameters provided are: - \( n = 50 \) - \( p = 0.3 \) #### Mean The mean (μ) of a binomial distribution is calculated using the formula: \[ \mu = n \cdot p \] For this example: \[ \mu = 50 \cdot 0.3 \] \[ \mu = 15 \] (Note: The value should be rounded to the nearest tenth if necessary.) #### Variance The variance (σ²) of a binomial distribution is calculated using the formula: \[ \sigma^2 = n \cdot p \cdot (1 - p) \] Plugging in the values: \[ \sigma^2 = 50 \cdot 0.3 \cdot (1 - 0.3) \] \[ \sigma^2 = 50 \cdot 0.3 \cdot 0.7 \] \[ \sigma^2 = 10.5 \] #### Standard Deviation The standard deviation (σ) is the square root of the variance: \[ \sigma = \sqrt{n \cdot p \cdot (1 - p)} \] Using the calculated variance: \[ \sigma = \sqrt{10.5} \] \[ \sigma \approx 3.24 \] #### Input Instructions Enter your answer in the answer box and then click "Check Answer". ### Example Screen Layout - **Remaining Parts**: 2 parts remaining shown in a progress bar. - **Action Buttons**: Clear All and Check Answer. The example screen captures a typical educational website layout where students input their calculated answers based on provided formulas. Ensure the values are rounded as specified in the instructions. --- This content guides students through the statistical concepts and computational steps necessary to characterize a binomial distribution's behavior. Understanding these basics are crucial for interpreting and analyzing binomial data effectively.
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