Two raw data sets of size 10 each are given in two variables xi and yi, i=2024 to i=2033 satisfying ∑i=20242033xi=235, ∑i=20242033yi=250, ∑i=20242033xi2=6750, ∑i=20242033yi2=6840 . The standard deviation of the data sets will be

∑x=235,∑y=250,∑x2=6750,∑y2=6840 ⇒σ2=110∑xi2−(∑xi10)2=110.6750−(23510)2=675−552.25=122.75⇒σ=11.08Similarly, for Σy=250,n=10,Σy2=6840

Two raw data sets of size 10 each are given in two variables xi and yi, i=2024 to i=2033 satisfying ∑i=20242033xi=235, ∑i=20242033yi=250, ∑i=20242033xi2=6750, ∑i=20242033yi2=6840 . The standard deviation of the data sets will be

∑x=235,∑y=250,∑x2=6750,∑y2=6840 ⇒σ2=110∑xi2−(∑xi10)2=110.6750−(23510)2=675−552.25=122.75⇒σ=11.08Similarly, for Σy=250,n=10,Σy2=6840

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Two raw data sets of size 10 each are given in two variables $x_{i}$ and $y_{i}$ , $i = 2024$ to $i = 2033$ satisfying $\sum_{i = 2024}^{2033} x_{i} = 235,$ $\sum_{i = 2024}^{2033} y_{i} = 250, \sum_{i = 2024}^{2033} {x_{i}}^{2} = 6750,$ $\sum_{i = 2024}^{2033} {y_{i}}^{2} = 6840$ . The standard deviation of the data sets will be

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11.08,7.58

11.02,7.58

11.08,7.68

11.48,7.48

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$\sum x = 235, \sum y = 250, \sum x^{2} = 6750, \sum y^{2} = 6840 \Rightarrow σ^{2} = \frac{1}{10} \sum x_{i}^{2} - {(\frac{\sum x_{i}}{10})}^{2} = \frac{1}{10} .6750 - {(\frac{235}{10})}^{2} = 675 - 552.25 = 122.75 \Rightarrow σ = 11.08$

Similarly, for $Σ y = 250, n = 10, Σ y^{2} = 6840$

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Two raw data sets of size 10 each are given in two variables xi and yi, i=2024 to i=2033 satisfying ∑i=20242033xi=235, ∑i=20242033yi=250, ∑i=20242033xi2=6750, ∑i=20242033yi2=6840 . The standard deviation of the data sets will be

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