Respuesta :
Mean:
[tex]\begin{gathered} \bar{x}=\frac{3.3+4.1+3.9+2.5+4.7+5.2+4.5+3.5+3.6+6.3+3.5+4.9+4.6+5.0+2.8+3.6+2.1+3.9+5.3+2.8}{20} \\ \\ \bar{x}=4.005 \end{gathered}[/tex]Standard deviation:
[tex]s=\sqrt[]{\frac{\Sigma(x_i-\bar{x})^2}{n-1}}[/tex]Step by step:
1. Deviation: Subtract the mean from each data:
[tex]\begin{gathered} (x_i-\bar{x}) \\ \\ 3.3-4.005=-0.705 \\ 4.1-4.005=0.095 \\ 3.9-4.005=-0.105 \\ 2.5-4.005=-1.505 \\ 4.7-4.005=0.695 \\ 5.2-4.005=1.195 \\ 4.5-4.005=0.495 \\ 3.5-4.005=-0.505 \\ 3.6-4.005=-0.405 \\ 6.3-4.005=2.295 \\ 3.5-4.005=-0.505 \\ 4.9-4.005=0.895 \\ 4.6-4.005=0.595 \\ 5.0-4.005=0.995 \\ 2.8-4.005=-1.205 \\ 3.6-4.005=-0.405 \\ 2.1-4.005=-1.905 \\ 3.9-4.005=-0.105 \\ 5.3-4.005=1.295 \\ 2.8-4.005=-1.205 \end{gathered}[/tex]2. Square each deviation:
[tex]\begin{gathered} (x_i-\bar{x})^2 \\ \\ (-0.705)^2=0.497025 \\ (0.095)^2=9.025\times10^{-3} \\ (-0.105)^2=0.011025 \\ (-1.505)^2=2.265025 \\ (0.695)^2=0.483025 \\ (1.195)^2=1.428025 \\ (0.495)^2=0.245025 \\ (-0.505)^2=0.255025 \\ (-0.405)^2=0.164025 \\ (2.295)^2=5.267025 \\ (-0.505)^2=0.255025 \\ (0.895)^2=0.801025 \\ (0.595)^2=0.354025 \\ (0.995)^2=0.990025 \\ (-1.205)^2=1.452025 \\ (-0.405)^2=0.164025 \\ (-1.905)^2=3.629025 \\ (-0.105)^2=0.011025 \\ (1.295)^2=1.677025 \\ (-1.205)^2=1.452025 \end{gathered}[/tex]3. Add the square deviations:
[tex]\Sigma(x_i-\bar{x})^2=21.4095[/tex]4. Divide the sum by one less than the number of data and take the square root of it to finally get the standard deviation:
[tex]s=\sqrt[]{\frac{\Sigma(x_i-\bar{x})^2}{n-1}}=\sqrt{\frac{21.4095}{20-1}}=\sqrt{\frac{21.4095}{19}}=1.06[/tex]