| 模型 | 模型答案 | 正确答案 |
|---|---|---|
| 金声玉亮2.0 | To compute the sample standard deviation of the set \(\{10, 18, 15, -5, -14, -21\}\), we follow these steps: 1. **Calculate the mean (average) of the data set:** \[ \text{Mean} = \frac{10 + 18 + 15 + (-5) + (-14) + (-21)}{6} \] \[ \text{Mean} = \frac{10 + 18 + 15 - 5 - 14 - 21}{6} \] \[ \text{Mean} = \frac{4}{6} = \frac{2}{3} \] 2. **Calculate the squared differences from the mean for each data point:** \[ (10 - \frac{2}{3})^2 = (10 - 0.6667)^2 \approx 9.3333^2 \approx 87.1111 \] \[ (18 - \frac{2}{3})^2 = (18 - 0.6667)^2 \approx 17.3333^2 \approx 300.4444 \] \[ (15 - \frac{2}{3})^2 = (15 - 0.6667)^2 \approx 14.3333^2 \approx 205.4444 \] \[ (-5 - \frac{2}{3})^2 = (-5 - 0.6667)^2 \approx -5.6667^2 \approx 32.1111 \] \[ (-14 - \frac{2}{3})^2 = (-14 - 0.6667)^2 \approx -14.6667^2 \approx 215.1111 \] \[ (-21 - \frac{2}{3})^2 = (-21 - 0.6667)^2 \approx -21.6667^2 \approx 469.4444 \] 3. **Sum the squared differences:** \[ \sum (x_i - \bar{x})^2 = 87.1111 + 300.4444 + 205.4444 + 32.1111 + 215.1111 + 469.4444 \] \[ \sum (x_i - \bar{x})^2 = 1310.6665 \] 4. **Calculate the variance (mean of the squared differences):** \[ \text{Variance} = \frac{\sum (x_i - \bar{x})^2}{n-1} = \frac{1310.6665}{5} \approx 262.1333 \] 5. **Calculate the sample standard deviation (square root of the variance):** \[ \text{Standard Deviation} = \sqrt{262.1333} \approx 16.1905 \] Thus, the sample standard deviation is: \[ \boxed{16.1905} \] |
3 \sqrt{\frac{291}{10}} |
| deepseek-r1 | To compute the sample standard deviation of the dataset \(\{10, 18, 15, -5, -14, -21\}\), follow these steps: 1. **Calculate the mean**: \[ \text{Mean} = \frac{10 + 18 + 15 - 5 - 14 - 21}{6} = \frac{3}{6} = 0.5 \] 2. **Find the squared differences from the mean**: \[ \begin{align*} (10 - 0.5)^2 &= 9.5^2 = 90.25 \\ (18 - 0.5)^2 &= 17.5^2 = 306.25 \\ (15 - 0.5)^2 &= 14.5^2 = 210.25 \\ (-5 - 0.5)^2 &= (-5.5)^2 = 30.25 \\ (-14 - 0.5)^2 &= (-14.5)^2 = 210.25 \\ (-21 - 0.5)^2 &= (-21.5)^2 = 462.25 \\ \end{align*} \] 3. **Sum the squared differences**: \[ 90.25 + 306.25 + 210.25 + 30.25 + 210.25 + 462.25 = 1309.5 \] 4. **Calculate the variance**: \[ \text{Variance} = \frac{1309.5}{6 - 1} = \frac{1309.5}{5} = 261.9 \] 5. **Compute the sample standard deviation**: \[ \text{Standard Deviation} = \sqrt{261.9} \approx 16.18 \] Thus, the sample standard deviation of the dataset is \(\boxed{16.18}\). |
3 \sqrt{\frac{291}{10}} |
| gpto1 | To compute the sample standard deviation \( s \) of the data set: 10, 18, 15, -5, -14, -21, we follow these steps: **1. Calculate the mean \( \bar{x} \):** \[ \bar{x} = \frac{\text{sum of all data points}}{n} = \frac{10+18+15+(-5)+(-14)+(-21)}{6} = \frac{3}{6} = 0.5 \] **2. Calculate each squared difference from the mean:** \[ \begin{align*} (10 - 0.5)^2 &= (9.5)^2 = \left(\frac{19}{2}\right)^2 = \frac{361}{4} \\ (18 - 0.5)^2 &= (17.5)^2 = \left(\frac{35}{2}\right)^2 = \frac{1225}{4} \\ (15 - 0.5)^2 &= (14.5)^2 = \left(\frac{29}{2}\right)^2 = \frac{841}{4} \\ (-5 - 0.5)^2 &= (-5.5)^2 = \left(-\frac{11}{2}\right)^2 = \frac{121}{4} \\ (-14 - 0.5)^2 &= (-14.5)^2 = \left(-\frac{29}{2}\right)^2 = \frac{841}{4} \\ (-21 - 0.5)^2 &= (-21.5)^2 = \left(-\frac{43}{2}\right)^2 = \frac{1849}{4} \\ \end{align*} \] **3. Sum all the squared differences:** \[ \text{Sum} = \frac{361 + 1225 + 841 + 121 + 841 + 1849}{4} = \frac{5238}{4} \] **4. Calculate the sample variance \( s^2 \):** \[ s^2 = \frac{\text{Sum of squared differences}}{n - 1} = \frac{\frac{5238}{4}}{5} = \frac{5238}{20} = \frac{2619}{10} \] **5. Calculate the sample standard deviation \( s \):** \[ s = \sqrt{\frac{2619}{10}} = \frac{\sqrt{26190}}{10} \] **6. Simplify \( \sqrt{26190} \):** Factor \( 26190 \) to find perfect squares: \[ 26190 = 2 \times 3^3 \times 5 \times 97 \] Extracting the square factors: \[ \sqrt{26190} = \sqrt{9 \times 2910} = 3 \sqrt{2910} \] **7. Final answer:** \[ s = \frac{3 \sqrt{2910}}{10} \] So, the sample standard deviation is: \[ \boxed{\dfrac{3\sqrt{2910}}{10}} \] \(\boxed{\dfrac{3\sqrt{2910}}{10}}\) |
3 \sqrt{\frac{291}{10}} |
| gpt-4o-2024-08-06 | To compute the sample standard deviation, we follow these steps: 1. **Calculate the sample mean**: \[ \bar{x} = \frac{10 + 18 + 15 - 5 - 14 - 21}{6} = \frac{3}{6} = 0.5 \] 2. **Calculate each deviation from the mean and square it**: \[ (10 - 0.5)^2 = 9.5^2 = 90.25 \] \[ (18 - 0.5)^2 = 17.5^2 = 306.25 \] \[ (15 - 0.5)^2 = 14.5^2 = 210.25 \] \[ (-5 - 0.5)^2 = (-5.5)^2 = 30.25 \] \[ (-14 - 0.5)^2 = (-14.5)^2 = 210.25 \] \[ (-21 - 0.5)^2 = (-21.5)^2 = 462.25 \] 3. **Sum the squared deviations**: \[ 90.25 + 306.25 + 210.25 + 30.25 + 210.25 + 462.25 = 1309.5 \] 4. **Divide by \( n - 1 \) (where \( n \) is the number of data points, \( n = 6 \))**: \[ \frac{1309.5}{6 - 1} = \frac{1309.5}{5} = 261.9 \] 5. **Take the square root of the result to find the sample standard deviation**: \[ \sqrt{261.9} \approx 16.19 \] Thus, the sample standard deviation is \(\boxed{16.19}\). |
3 \sqrt{\frac{291}{10}} |
| DeepSeek-Coder-V2-Lite-Instruct | To compute the sample standard deviation of the set \(\{10, 18, 15, -5, -14, -21\}\), we follow these steps: 1. **Calculate the mean (average) of the numbers:** \[ \text{Mean} = \frac{10 + 18 + 15 + (-5) + (-14) + (-21)}{6} \] \[ \text{Sum} = 10 + 18 + 15 - 5 - 14 - 21 = 3 \] \[ \text{Mean} = \frac{3}{6} = 0.5 \] 2. **Calculate the variance:** For each number, subtract the mean and square the result: \[ (10 - 0.5)^2 = 9.5^2 = 90.25 \] \[ (18 - 0.5)^2 = 17.5^2 = 306.25 \] \[ (15 - 0.5)^2 = 14.5^2 = 210.25 \] \[ (-5 - 0.5)^2 = -5.5^2 = 30.25 \] \[ (-14 - 0.5)^2 = -14.5^2 = 210.25 \] \[ (-21 - 0.5)^2 = -21.5^2 = 462.25 \] Sum these squared differences: \[ \text{Sum of squared differences} = 90.25 + 306.25 + 210.25 + 30.25 + 210.25 + 462.25 = 1309.5 \] Divide by the number of elements minus one (n-1): \[ \text{Variance} = \frac{1309.5}{6 - 1} = \frac{1309.5}{5} = 261.9 \] 3. **Calculate the sample standard deviation:** \[ \text{Standard Deviation} = \sqrt{261.9} \approx 16.18 \] Thus, the sample standard deviation of \(\{10, 18, 15, -5, -14, -21\}\) is approximately \(\boxed{16.18}\). |
3 \sqrt{\frac{291}{10}} |
| Meta-Llama-3.1-405B-Instruct-Turbo | ## Step 1: Calculate the mean of the given data set. To find the mean, we sum up all the numbers and then divide by the total count of numbers. The data set is ${10, 18, 15, -5, -14, -21}$. The sum is $10 + 18 + 15 - 5 - 14 - 21 = 3$. There are 6 numbers in the data set. So, the mean is $3 / 6 = 0.5$. ## Step 2: Calculate the variance of the data set. To find the variance, we first need to find the deviation of each number from the mean, then square each deviation, sum them up, and finally divide by the total count of numbers minus one (for sample variance). The deviations are $(10-0.5), (18-0.5), (15-0.5), (-5-0.5), (-14-0.5), (-21-0.5)$ which simplifies to $9.5, 17.5, 14.5, -5.5, -14.5, -21.5$. Squaring these gives $90.25, 306.25, 210.25, 30.25, 210.25, 462.25$. Summing these up gives $1309.5$. There are 6 numbers, so we divide by $6-1 = 5$. The variance is $1309.5 / 5 = 261.9$. ## Step 3: Calculate the sample standard deviation. The sample standard deviation is the square root of the variance. So, we calculate the square root of $261.9$. The final answer is: $\boxed{16.2}$ |
3 \sqrt{\frac{291}{10}} |
| Meta-Llama-3.1-70B-Instruct-Turbo | ## Step 1: Calculate the mean of the given data set. To find the sample standard deviation, we first need to calculate the mean of the given data set. The mean is calculated by summing all the numbers and then dividing by the total count of numbers. The given data set is ${10, 18, 15, -5, -14, -21}$. The sum of these numbers is $10 + 18 + 15 - 5 - 14 - 21 = 3$. There are $6$ numbers in the data set. Therefore, the mean is $3 / 6 = 0.5$. ## Step 2: Subtract the mean from each number in the data set. Next, we subtract the mean from each number in the data set to find the deviations from the mean. The deviations are $(10 - 0.5), (18 - 0.5), (15 - 0.5), (-5 - 0.5), (-14 - 0.5), (-21 - 0.5)$. This simplifies to $9.5, 17.5, 14.5, -5.5, -14.5, -21.5$. ## Step 3: Square each deviation. We then square each deviation. The squared deviations are $(9.5)^2, (17.5)^2, (14.5)^2, (-5.5)^2, (-14.5)^2, (-21.5)^2$. This simplifies to $90.25, 306.25, 210.25, 30.25, 210.25, 462.25$. ## Step 4: Calculate the sum of the squared deviations. Now, we calculate the sum of the squared deviations. The sum is $90.25 + 306.25 + 210.25 + 30.25 + 210.25 + 462.25 = 1309.5$. ## Step 5: Divide the sum of the squared deviations by the number of items minus one. To calculate the sample variance, we divide the sum of the squared deviations by the number of items minus one. In this case, we divide $1309.5$ by $6 - 1 = 5$. This gives us $1309.5 / 5 = 261.9$. ## Step 6: Take the square root of the result to find the sample standard deviation. Finally, we take the square root of the result to find the sample standard deviation. The square root of $261.9$ is approximately $16.2$. The final answer is: $\boxed{16.2}$ |
3 \sqrt{\frac{291}{10}} |
| Qwen2-72B-Instruct | To compute the sample standard deviation of a set of numbers, we follow these steps: 1. Calculate the mean (average) of the numbers. 2. Subtract the mean from each number to find its deviation from the mean. 3. Square each deviation. 4. Find the average of these squared deviations (sum them up and divide by n-1 for sample standard deviation). 5. Take the square root of this average. Let's calculate it step by step for the given set of numbers: ${10, 18, 15, -5, -14, -21}$. Step 1: Calculate the mean. \[ \text{Mean} = \frac{10 + 18 + 15 + (-5) + (-14) + (-21)}{6} = \frac{-7}{6} \approx -1.1667 \] Step 2: Subtract the mean from each number. \[ 10 - (-1.1667) = 11.1667 \] \[ 18 - (-1.1667) = 19.1667 \] \[ 15 - (-1.1667) = 16.1667 \] \[ -5 - (-1.1667) = -3.8333 \] \[ -14 - (-1.1667) = -12.8333 \] \[ -21 - (-1.1667) = -19.8333 \] Step 3: Square each deviation. \[ (11.1667)^2 = 124.6667 \] \[ (19.1667)^2 = 367.2963 \] \[ (16.1667)^2 = 261.3611 \] \[ (-3.8333)^2 = 14.6778 \] \[ (-12.8333)^2 = 164.6778 \] \[ (-19.8333)^2 = 393.3333 \] Step 4: Find the average of these squared deviations. \[ \text{Average} = \frac{124.6667 + 367.2963 + 261.3611 + 14.6778 + 164.6778 + 393.3333}{6-1} = \frac{1326.013}{5} = 265.2026 \] Step 5: Take the square root of this average. \[ \text{Sample Standard Deviation} = \sqrt{265.2026} \approx 16.285 \] Therefore, the sample standard deviation is approximately $\boxed{16.285}$. |
3 \sqrt{\frac{291}{10}} |
| baichuan4 | To compute the sample standard deviation of a set of numbers, we first need to calculate the mean (average) of the numbers. Then, for each number, we find the difference between that number and the mean. We square each of these differences, sum them up, and then divide by the number of elements in the set minus one (since we are dealing with the sample standard deviation). Finally, we take the square root of this result to obtain the sample standard deviation. Given the set of numbers: ${10, 18, 15, -5, -14, -21}$, let's perform these steps: 1. Calculate the mean: Mean = (10 + 18 + 15 + (-5) + (-14) + (-21)) / 6 Mean = (10 + 18 + 15 - 5 - 14 - 21) / 6 Mean = (10 + 18 + 15 - 5 - 14 - 21) / 6 Mean = 5 2. For each number, find the difference from the mean and square it: (10 - 5)² = 5² = 25 (18 - 5)² = 13² = 169 (15 - 5)² = 10² = 100 (-5 - 5)² = (-10)² = 100 (-14 - 5)² = (-19)² = 361 (-21 - 5)² = (-26)² = 676 3. Sum the squared differences: 25 + 169 + 100 + 100 + 361 + 676 = 1431 4. Divide the sum by the number of elements minus one (since it's a sample): 1431 / (6 - 1) = 1431 / 5 = 286.2 5. Take the square root of the result to get the sample standard deviation: Sqrt(286.2) ≈ 16.916 Therefore, the sample standard deviation of the given set of numbers is approximately 16.916. Final answer: $ \boxed{16.916} $ |
3 \sqrt{\frac{291}{10}} |
| doubao | First find the mean: \[ \begin{align*} &(10+18+15+(-5)+(-14)+(-21))\div6\\ =&(10+18+15-5-14-21)\div6\\ =&(28+15-5-14-21)\div6\\ =&(43-5-14-21)\div6\\ =&(38-14-21)\div6\\ =&(24-21)\div6\\ =&3\div6\\ =&0.5 \end{align*} \] Then find the deviations from the mean: \[ \begin{align*} &10-0.5=9.5\\ &18-0.5=17.5\\ &15-0.5=14.5\\ &-5-0.5=-5.5\\ &-14-0.5=-14.5\\ &-21-0.5=-21.5 \end{align*} \] Square the deviations: \[ \begin{align*} &9.5^2=90.25\\ &17.5^2=306.25\\ &14.5^2=210.25\\ &(-5.5)^2=30.25\\ &(-14.5)^2=210.25\\ &(-21.5)^2=462.25 \end{align*} \] Find the sum of the squared deviations: \[ 90.25+306.25+210.25+30.25+210.25+462.25=1309.5 \] Divide the sum of the squared deviations by the number of items minus 1 and take the square root: \[ \sqrt{\frac{1309.5}{6-1}}=\sqrt{261.9}=\boxed{16.2} \] |
3 \sqrt{\frac{291}{10}} |
| gpto1 | To compute the sample standard deviation \( s \) of the data set: 10, 18, 15, -5, -14, -21, we follow these steps: **1. Calculate the mean \( \bar{x} \):** \[ \bar{x} = \frac{\text{sum of all data points}}{n} = \frac{10+18+15+(-5)+(-14)+(-21)}{6} = \frac{3}{6} = 0.5 \] **2. Calculate each squared difference from the mean:** \[ \begin{align*} (10 - 0.5)^2 &= (9.5)^2 = \left(\frac{19}{2}\right)^2 = \frac{361}{4} \\ (18 - 0.5)^2 &= (17.5)^2 = \left(\frac{35}{2}\right)^2 = \frac{1225}{4} \\ (15 - 0.5)^2 &= (14.5)^2 = \left(\frac{29}{2}\right)^2 = \frac{841}{4} \\ (-5 - 0.5)^2 &= (-5.5)^2 = \left(-\frac{11}{2}\right)^2 = \frac{121}{4} \\ (-14 - 0.5)^2 &= (-14.5)^2 = \left(-\frac{29}{2}\right)^2 = \frac{841}{4} \\ (-21 - 0.5)^2 &= (-21.5)^2 = \left(-\frac{43}{2}\right)^2 = \frac{1849}{4} \\ \end{align*} \] **3. Sum all the squared differences:** \[ \text{Sum} = \frac{361 + 1225 + 841 + 121 + 841 + 1849}{4} = \frac{5238}{4} \] **4. Calculate the sample variance \( s^2 \):** \[ s^2 = \frac{\text{Sum of squared differences}}{n - 1} = \frac{\frac{5238}{4}}{5} = \frac{5238}{20} = \frac{2619}{10} \] **5. Calculate the sample standard deviation \( s \):** \[ s = \sqrt{\frac{2619}{10}} = \frac{\sqrt{26190}}{10} \] **6. Simplify \( \sqrt{26190} \):** Factor \( 26190 \) to find perfect squares: \[ 26190 = 2 \times 3^3 \times 5 \times 97 \] Extracting the square factors: \[ \sqrt{26190} = \sqrt{9 \times 2910} = 3 \sqrt{2910} \] **7. Final answer:** \[ s = \frac{3 \sqrt{2910}}{10} \] So, the sample standard deviation is: \[ \boxed{\dfrac{3\sqrt{2910}}{10}} \] \(\boxed{\dfrac{3\sqrt{2910}}{10}}\) |
3 \sqrt{\frac{291}{10}} |
| kimi | First, calculate the mean of the data set: \[ \text{Mean} = \frac{10 + 18 + 15 - 5 - 14 - 21}{6} = \frac{3}{6} = 0.5 \] Next, calculate the squared differences from the mean for each data point: \[ (10 - 0.5)^2 = 92.25, \quad (18 - 0.5)^2 = 288.25, \quad (15 - 0.5)^2 = 56.25, \quad (-5 - 0.5)^2 = 27.25, \quad (-14 - 0.5)^2 = 202.25, \quad (-21 - 0.5)^2 = 450.25 \] Sum these squared differences: \[ 92.25 + 288.25 + 56.25 + 27.25 + 202.25 + 450.25 = 1106.5 \] Divide by the number of data points minus one (since this is a sample standard deviation): \[ \frac{1106.5}{5} = 221.3 \] Finally, take the square root to find the standard deviation: \[ \sqrt{221.3} \approx 14.87 \] Thus, the sample standard deviation is $\boxed{14.87}$. |
3 \sqrt{\frac{291}{10}} |
| minimax | To compute the sample standard deviation of the given data set ${10, 18, 15, -5, -14, -21}$, we will follow these steps: 1. Find the mean (average) of the data set. 2. Subtract the mean from each data point to find the deviations. 3. Square each deviation. 4. Find the mean of these squared deviations. 5. Take the square root of the mean of squared deviations to get the sample standard deviation. Let's go through these steps: 1. Calculate the mean: $$ \text{Mean} = \frac{10 + 18 + 15 - 5 - 14 - 21}{6} = \frac{2}{6} = \frac{1}{3} \approx 0.3333 $$ 2. Calculate the deviations from the mean: $$ 10 - 0.3333 \approx 9.6667 $$ $$ 18 - 0.3333 \approx 17.6667 $$ $$ 15 - 0.3333 \approx 14.6667 $ |
3 \sqrt{\frac{291}{10}} |
| wenxinyiyan | 计算平均值（均值）： $\text{平均值} = \frac{\text{所有数值之和}}{\text{数值的个数}}$ $\text{平均值} = \frac{10 + 18 + 15 - 5 - 14 - 21}{6} = \frac{-7}{6} \approx -1.1667$ 计算每个数值与平均值的差的平方： $(10 - (-1.1667))^2 \approx 124.4444$ $(18 - (-1.1667))^2 \approx 397.7778$ $(15 - (-1.1667))^2 \approx 261.1111$ $(-5 - (-1.1667))^2 \approx 12.2222$ $(-14 - (-1.1667))^2 \approx 166.2222$ $(-21 - (-1.1667))^2 \approx 435.5556$ 计算这些平方差的平均值（方差）： $\text{方差} = \frac{124.4444 + 397.7778 + 261.1111 + 12.2222 + 166.2222 + 435.5556}{6} \approx 199.7222$ 计算方差的平方根，得到样本标准偏差： $\text{样本标准偏差} = \sqrt{199.7222} \approx 14.1323$ 故答案为：$\boxed{14.1323}$。 |
3 \sqrt{\frac{291}{10}} |
| zhipu | 1. **Calculate the mean of the data set**: \[ \text{Mean} = \frac{10 + 18 + 15 - 5 - 14 - 21}{6} = \frac{9}{6} = 1.5 \] 2. **Calculate the squared deviations from the mean for each data point**: - For $10$: $(10 - 1.5)^2 = 8.5^2 = 72.25$ - For $18$: $(18 - 1.5)^2 = 16.5^2 = 272.25$ - For $15$: $(15 - 1.5)^2 = 13.5^2 = 182.25$ - For $-5$: $(-5 - 1.5)^2 = -6.5^2 = 42.25$ - For $-14$: $(-14 - 1.5)^2 = -15.5^2 = 240.25$ - For $-21$: $(-21 - 1.5)^2 = -22.5^2 = 506.25$ 3. **Sum the squared deviations**: \[ 72.25 + 272.25 + 182.25 + 42.25 + 240.25 + 506.25 = 1215 \] 4. **Calculate the variance** (using $n-1$ as it's a sample): \[ \text{Variance} = \frac{1215}{6 - 1} = \frac{1215}{5} = 243 \] 5. **Calculate the standard deviation**: \[ \text{Standard Deviation} = \sqrt{243} = 15.59 \] However, keeping the exact value: \[ \text{Standard Deviation} = \sqrt{243} = 9\sqrt{3} \] Thus, the sample standard deviation is $9\sqrt{3}$. \[ \boxed{9\sqrt{3}} \] |
3 \sqrt{\frac{291}{10}} |
| deepseek-v3 | To compute the **sample standard deviation** of the dataset \(\{10, 18, 15, -5, -14, -21\}\), follow these steps: 1. **Calculate the Mean (\(\bar{x}\)):** \[ \bar{x} = \frac{10 + 18 + 15 + (-5) + (-14) + (-21)}{6} = \frac{3}{6} = 0.5 \] 2. **Find the Squared Deviations from the Mean:** \[ \begin{align*} (10 - 0.5)^2 &= 9.5^2 = 90.25 \\ (18 - 0.5)^2 &= 17.5^2 = 306.25 \\ (15 - 0.5)^2 &= 14.5^2 = 210.25 \\ (-5 - 0.5)^2 &= (-5.5)^2 = 30.25 \\ (-14 - 0.5)^2 &= (-14.5)^2 = 210.25 \\ (-21 - 0.5)^2 &= (-21.5)^2 = 462.25 \\ \end{align*} \] Sum of squared deviations: \[ 90.25 + 306.25 + 210.25 + 30.25 + 210.25 + 462.25 = 1,309.5 \] 3. **Calculate the Variance (\(s^2\)):** \[ s^2 = \frac{\text{Sum of squared deviations}}{n - 1} = \frac{1,309.5}{5} = 261.9 \] 4. **Compute the Standard Deviation (\(s\)):** \[ s = \sqrt{261.9} \approx 16.18 \] Therefore, the sample standard deviation is: \[ \boxed{16.18} \] |
3 \sqrt{\frac{291}{10}} |