Statistics

Exercise 13.2 • Variance & Standard Deviation
Key Formulas:
Variance ($\sigma^2$) for Ungrouped: $\frac{\sum (x_i – \bar{x})^2}{n}$
Variance for Grouped: $\frac{1}{N} \sum f_i (x_i – \bar{x})^2$
Shortcut Method Variance: $h^2 \left[ \frac{1}{N} \sum f_i y_i^2 – \left(\frac{1}{N} \sum f_i y_i\right)^2 \right]$ where $y_i = \frac{x_i – A}{h}$
Standard Deviation ($\sigma$) = $\sqrt{\text{Variance}}$
Q1
1. Find Mean and Variance: 6, 7, 10, 12, 13, 4, 8, 12
Mean $\bar{x} = \frac{6+7+10+12+13+4+8+12}{8} = \frac{72}{8} = 9$.
Deviations $(x_i – 9)$: -3, -2, 1, 3, 4, -5, -1, 3.
Sq Devs 9, 4, 1, 9, 16, 25, 1, 9. Sum = 74.
Variance $\sigma^2 = \frac{74}{8} = 9.25$.
Mean = 9, Variance = 9.25
Q2
2. Find Mean and Variance of first n natural numbers.
Mean Sum $\sum x = \frac{n(n+1)}{2}$. Mean $\bar{x} = \frac{n+1}{2}$.
Variance Formula: $\sigma^2 = \frac{1}{n}\sum x^2 – (\bar{x})^2$.
$\sum x^2 = \frac{n(n+1)(2n+1)}{6}$.
Substitute $\sigma^2 = \frac{(n+1)(2n+1)}{6} – \left(\frac{n+1}{2}\right)^2 = \frac{n+1}{2} [\frac{2n+1}{3} – \frac{n+1}{2}]$.
Simplify $\frac{n+1}{2} [\frac{4n+2-3n-3}{6}] = \frac{n+1}{2} \cdot \frac{n-1}{6} = \frac{n^2-1}{12}$.
Mean = $\frac{n+1}{2}$, Variance = $\frac{n^2-1}{12}$
Q3
3. Find Mean and Variance of first 10 multiples of 3.
Data 3, 6, 9, 12, 15, 18, 21, 24, 27, 30. ($n=10$).
Mean Sum = $3(1+2+…+10) = 3(55) = 165$. $\bar{x} = 16.5$.
Sq Sum $\sum x^2 = 3^2(1^2+…+10^2) = 9(385) = 3465$.
Variance $\frac{3465}{10} – (16.5)^2 = 346.5 – 272.25 = 74.25$.
Mean = 16.5, Variance = 74.25
Q4
4. Find Mean and Variance (Discrete Frequency).
$x_i$ $f_i$ $f_ix_i$ $d_i = x_i – \bar{x}$ $f_id_i^2$
6212-13338
10440-9324
14798-5175
1812216-112
2481925200
2841129324
3039011363
Mean $\bar{x} = \frac{760}{40} = 19$.
Variance $\sigma^2 = \frac{1736}{40} = 43.4$.
Mean = 19, Variance = 43.4
Q5
5. Find Mean and Variance (Discrete Frequency).
$x_i$ $f_i$ $f_ix_i$ $d_i = x_i – 100$ $f_id_i^2$
923276-8192
932186-798
973291-327
982196-28
1026612224
1043312448
10933279243
Mean $\bar{x} = \frac{2200}{22} = 100$.
Variance $\sigma^2 = \frac{640}{22} = 29.09$.
Mean = 100, Variance = 29.09
Q6
6. Find Mean and Standard Deviation using Short-cut method.
$x_i$ $f_i$ $y_i = x_i – 64$ $f_iy_i$ $f_iy_i^2$
602-4-832
611-3-39
6212-2-2448
6329-1-2929
6425000
651211212
661022040
67431236
68542080
Mean $A + \frac{\sum f_iy_i}{N} = 64 + \frac{0}{100} = 64$.
Variance $\frac{286}{100} – (0)^2 = 2.86$.
Std Dev $\sqrt{2.86} \approx 1.69$.
Mean = 64, SD = 1.69
Q7
7. Find Mean and Variance (Grouped Data).
Class Mid ($x_i$) $f_i$ $y_i = \frac{x_i – 105}{30}$ $f_iy_i$ $f_iy_i^2$
0-30152-3-618
30-60453-2-612
60-90755-1-55
90-12010510000
120-1501353133
150-180165521020
180-21019523618
Mean $105 + \frac{2}{30} \times 30 = 107$.
Variance $30^2 [\frac{76}{30} – (\frac{2}{30})^2] = 900 [\frac{76}{30} – \frac{4}{900}] = 900 \frac{76}{30} – 4 = 2280 – 4 = 2276$.
Mean = 107, Variance = 2276
Q8
8. Find Mean and Variance (Grouped Data).
Class Mid ($x_i$) $f_i$ $y_i = \frac{x_i – 25}{10}$ $f_iy_i$ $f_iy_i^2$
0-1055-2-1020
10-20158-1-88
20-302515000
30-40351611616
40-5045621224
Mean $25 + \frac{10}{50} \times 10 = 25 + 2 = 27$.
Variance $10^2 [\frac{68}{50} – (\frac{10}{50})^2] = 100 [1.36 – 0.04] = 100(1.32) = 132$.
Mean = 27, Variance = 132
Q9
9. Mean, Variance and SD using Short-cut method (Height in cms).
Class Mid ($x_i$) $f_i$ $y_i = \frac{x_i – 92.5}{5}$ $f_iy_i$ $f_iy_i^2$
70-7572.53-4-1248
75-8077.54-3-1236
80-8582.57-2-1428
85-9087.57-1-77
90-9592.515000
95-10097.59199
100-105102.5621224
105-110107.5631854
110-115112.5341248
Mean $92.5 + \frac{6}{60} \times 5 = 92.5 + 0.5 = 93$.
Variance $5^2 [\frac{254}{60} – (\frac{6}{60})^2] = 25 [4.233 – 0.01] = 25(4.223) = 105.58$.
Std Dev $\sqrt{105.58} = 10.27$.
Mean = 93, Var = 105.58, SD = 10.27
Q10
10. Mean and Variance (Diameters of Circles).
Note Classes are inclusive. Midpoints: $\frac{33+36}{2}=34.5$, etc. Step $h=4$.
Class Mid ($x_i$) $f_i$ $y_i = \frac{x_i – 42.5}{4}$ $f_iy_i$ $f_iy_i^2$
33-3634.515-2-3060
37-4038.517-1-1717
41-4442.521000
45-4846.52212222
49-5250.525250100
Mean $42.5 + \frac{25}{100} \times 4 = 42.5 + 1 = 43.5$.
Variance $4^2 [\frac{199}{100} – (\frac{25}{100})^2] = 16 [1.99 – 0.0625] = 16(1.9275) = 30.84$.
Mean = 43.5, Variance = 30.84
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