QUESTION IMAGE
Question
determine the standard deviation ($\sigma$) by filling in the table as part of your calculation. consider the following data 6, 6, 10, 8, 10, 8
| $x$ | $\bar{x}$ | $x - \bar{x}$ | $(x - \bar{x})^2$ |
a. 1.63
b. 0.47
c. 0.94
d. 1.15
Step1: Calculate the mean
The data is 6, 6, 10, 8, 10, 8. The sum of the data is $6 + 6+10 + 8+10 + 8=48$. There are $n = 6$ data - points. The mean $\bar{x}=\frac{48}{6}=8$.
Step2: Calculate $x-\bar{x}$ and $(x - \bar{x})^2$ for each data - point
| $x$ | $\bar{x}$ | $x-\bar{x}$ | $(x - \bar{x})^2$ |
|---|---|---|---|
| 6 | 8 | $6 - 8=-2$ | $(-2)^2 = 4$ |
| 10 | 8 | $10 - 8 = 2$ | $2^2=4$ |
| 8 | 8 | $8 - 8 = 0$ | $0^2 = 0$ |
| 10 | 8 | $10 - 8 = 2$ | $2^2=4$ |
| 8 | 8 | $8 - 8 = 0$ | $0^2 = 0$ |
Step3: Calculate the variance
The variance $\sigma^{2}=\frac{\sum_{i = 1}^{n}(x_{i}-\bar{x})^{2}}{n}$. Here, $\sum_{i = 1}^{6}(x_{i}-\bar{x})^{2}=4 + 4+4 + 0+4 + 0 = 16$. So, $\sigma^{2}=\frac{16}{6}=\frac{8}{3}\approx2.67$.
Step4: Calculate the standard deviation
The standard deviation $\sigma=\sqrt{\sigma^{2}}=\sqrt{\frac{8}{3}}\approx1.63$.
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a. 1.63