In: Statistics and Probability
The standard deviation is equal to the square root of the average squared deviations about the mean. More succintly, it is equal to the square root of the variance. So one way to calculate the standard deviation of a frequency distribution is to calculate the variance. Complete the table below as the first step in calculating the variance:
(10 points)
X |
f |
X−x |
(X−x)2 |
96 |
1 | ||
94 |
1 | ||
92 |
1 | ||
87 |
1 | ||
85 |
1 | ||
84 |
1 | ||
83 |
1 | ||
82 |
1 | ||
79 |
1 | ||
78 |
1 | ||
76 |
1 | ||
73 |
1 | ||
72 |
1 | ||
69 |
2 | ||
67 |
2 | ||
66 |
1 | ||
63 |
1 | ||
62 |
1 | ||
61 |
2 | ||
51 |
1 | ||
44 |
1 | ||
42 |
1 |
Solution-:
We prepare following table by using MS-Excel :
x | f | fi*xi | (x-xbar) | (x-xbar)^2 | fi*(x-xbar)^2 | fi*xi^2 |
96 | 1 | 96 | 23.88 | 570.2544 | 570.25 | 9216 |
94 | 1 | 94 | 21.88 | 478.7344 | 478.73 | 8836 |
92 | 1 | 92 | 19.88 | 395.2144 | 395.21 | 8464 |
87 | 1 | 87 | 14.88 | 221.4144 | 221.41 | 7569 |
85 | 1 | 85 | 12.88 | 165.8944 | 165.89 | 7225 |
84 | 1 | 84 | 11.88 | 141.1344 | 141.13 | 7056 |
83 | 1 | 83 | 10.88 | 118.3744 | 118.37 | 6889 |
82 | 1 | 82 | 9.88 | 97.6144 | 97.61 | 6724 |
79 | 1 | 79 | 6.88 | 47.3344 | 47.33 | 6241 |
78 | 1 | 78 | 5.88 | 34.5744 | 34.57 | 6084 |
76 | 1 | 76 | 3.88 | 15.0544 | 15.05 | 5776 |
73 | 1 | 73 | 0.88 | 0.7744 | 0.77 | 5329 |
72 | 1 | 72 | -0.12 | 0.0144 | 0.01 | 5184 |
69 | 2 | 138 | -3.12 | 9.7344 | 19.47 | 9522 |
67 | 2 | 134 | -5.12 | 26.2144 | 52.43 | 8978 |
66 | 1 | 66 | -6.12 | 37.4544 | 37.45 | 4356 |
63 | 1 | 63 | -9.12 | 83.1744 | 83.17 | 3969 |
62 | 1 | 62 | -10.12 | 102.4144 | 102.41 | 3844 |
61 | 2 | 122 | -11.12 | 123.6544 | 247.31 | 7442 |
51 | 1 | 51 | -21.12 | 446.0544 | 446.05 | 2601 |
44 | 1 | 44 | -28.12 | 790.7344 | 790.73 | 1936 |
42 | 1 | 42 | -30.12 | 907.2144 | 907.21 | 1764 |
Total | 25 | 1803 | 4972.64 | 135005 |
From this table we get,
and
The standard deviation is equal to the square root of the average squared deviations about the mean.
Or
it is equal to the square root of the variance.