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Describe the process of calculating a standard deviation. Give a simple example of its calculation (such as calculating the standard deviation of the numbers \( 2,3,4,4 \), and 6 ). What is the standard deviation if all of the sample values are the same? Fill in the blanks to complete the process of calculating a standard deviation. Compute the mean of the data set. Then find the deviation from the mean for every data value by subtracting the mean from the data value. Find the squares of all the deviations from the mean, and then add them together. Divide this sum by the total number of data values minus 1 . The standard deviation is the square root of this quotient. The standard deviation of the numbers \( 2,3,4,4 \), and 6 is approximately (Round to three decimal places as needed.)

Ask by Newton Bowen. in the United States
Mar 19,2025

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**Calculating Standard Deviation:** 1. **Compute the mean:** For numbers \( 2, 3, 4, 4, 6 \), the mean is \( 3.8 \). 2. **Find deviations from the mean:** \( 2 - 3.8 = -1.8 \), \( 3 - 3.8 = -0.8 \), \( 4 - 3.8 = 0.2 \), \( 4 - 3.8 = 0.2 \), \( 6 - 3.8 = 2.2 \). 3. **Square each deviation:** \( (-1.8)^2 = 3.24 \), \( (-0.8)^2 = 0.64 \), \( (0.2)^2 = 0.04 \), \( (0.2)^2 = 0.04 \), \( (2.2)^2 = 4.84 \). 4. **Sum the squared deviations:** \( 3.24 + 0.64 + 0.04 + 0.04 + 4.84 = 8.8 \). 5. **Divide by \( n-1 \) (where \( n = 5 \)):** \( 8.8 \div 4 = 2.2 \). 6. **Take the square root of the variance:** \( \sqrt{2.2} \approx 1.483 \). **Standard Deviation:** The standard deviation of \( 2, 3, 4, 4, 6 \) is approximately **1.483**. **If all sample values are the same:** The standard deviation is **0**.

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First, let's compute the mean of the numbers \( 2, 3, 4, 4, \) and \( 6 \). The mean is calculated as follows: \[ \text{Mean} = \frac{(2 + 3 + 4 + 4 + 6)}{5} = \frac{19}{5} = 3.8. \] Next, we find the deviations from the mean: - \( 2 - 3.8 = -1.8 \) - \( 3 - 3.8 = -0.8 \) - \( 4 - 3.8 = 0.2 \) - \( 4 - 3.8 = 0.2 \) - \( 6 - 3.8 = 2.2 \) Now we square these deviations: - \( (-1.8)^2 = 3.24 \) - \( (-0.8)^2 = 0.64 \) - \( (0.2)^2 = 0.04 \) - \( (0.2)^2 = 0.04 \) - \( (2.2)^2 = 4.84 \) Adding these squares together: \[ 3.24 + 0.64 + 0.04 + 0.04 + 4.84 = 8.80. \] Next, we divide this sum by the total number of data values minus 1: \[ \frac{8.80}{5-1} = \frac{8.80}{4} = 2.20. \] Finally, the standard deviation is the square root of this quotient: \[ \sqrt{2.20} \approx 1.483. \] The standard deviation of the numbers \( 2, 3, 4, 4, \) and \( 6 \) is approximately \( 1.483 \) (rounded to three decimal places). Now, if all the sample values are the same, for example, a set of numbers like \( 5, 5, 5, 5 \), the deviations from the mean would all be zero. Thus, the standard deviation would also be zero. This signifies that there is no variability in the data set! Fun fact: The more similar the values are, the lower the standard deviation. It's like a party where everyone wears the same outfit—no diversity in style means zero "fashion standard deviation"!

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