Question:

For two groups of 15 sizes each, mean and variance of first group is 12, 14 respectively, and second group has mean 14 and variance of σ2. If combined variance is 13 then find variance of second group?

Updated On: Mar 21, 2025
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The Correct Option is C

Approach Solution - 1

\(\bar{x}\) = 12, \(\sigma _{1}^{2}\) = 14, \(\bar{y}\) = 12, \(\sigma _{2}^{2}\) = \(\sigma ^{2}\), n1 = n2 = 15
\(\sigma _{1}^{2}\) = 14 = \(\sum \frac{x_{i}^{2}}{15}-(12)^{2}\Rightarrow \sum x_{i}^{2}=2370, \sum x_{i}=180\)
\(\sigma _{2}^{2}=\sum \frac{y_{i}^{2}}{15}-(14)^{2}, \sum y_{i}=210\)
13 = \(\frac{\sum x_{i}^{2}\sum y_{i}^{2}}{30}-(\frac{15\bar{x}+15\bar{y}}{30})^{2}\)
\(\frac{2370+\sum y_{i}^{2}}{30}-(13)^{2}\)
\(\sum y_{i}^{2}=3090\Rightarrow \sigma _{2}^{2}=\frac{3090}{15}-(14)^{2}=10\)
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Approach Solution -2

Combined Variance Calculation 

Let $n_1$ and $n_2$ be the number of elements in the first and second sets, respectively.
Let $m_1$ and $m_2$ be the means of the first and second sets, respectively.
Let $\sigma_1^2$ and $\sigma_2^2$ be the variances of the first and second sets, respectively. We are given $n_1 = n_2 = 15$, $m_1 = 12$, $m_2 = 14$, $\sigma_1^2 = 14$, and $\sigma_2^2 = \sigma^2$.

The combined variance of the two sets is given by: \[ \sigma_c^2 = \frac{n_1\sigma_1^2 + n_2\sigma_2^2}{n_1 + n_2} + \frac{n_1n_2(m_1 - m_2)^2}{(n_1 + n_2)^2}. \]

We are given that the combined variance $\sigma_c^2 = 13$. Plugging in the given values: \[ 13 = \frac{15(14) + 15\sigma^2}{15 + 15} + \frac{15 \cdot 15(12 - 14)^2}{(15 + 15)^2} \] \[ 13 = \frac{210 + 15\sigma^2}{30} + \frac{225(4)}{900} \] \[ 13 = \frac{210 + 15\sigma^2}{30} + \frac{900}{900} \] \[ 13 = \frac{210 + 15\sigma^2}{30} + 1 \] \[ 12 = \frac{210 + 15\sigma^2}{30} \] \[ 360 = 210 + 15\sigma^2\] \[ 150 = 15\sigma^2\] \[ 10 = \sigma^2. \] Therefore, $\sigma^2 = 10$.

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Concepts Used:

Variance and Standard Deviation

Variance:

According to layman’s words, the variance is a measure of how far a set of data are dispersed out from their mean or average value. It is denoted as ‘σ2’.

Variance Formula:

Read More: Difference Between Variance and Standard Deviation

Standard Deviation:

The spread of statistical data is measured by the standard deviation. Distribution measures the deviation of data from its mean or average position. The degree of dispersion is computed by the method of estimating the deviation of data points. It is denoted by the symbol, ‘σ’.

Types of Standard Deviation:

  • Standard Deviation for Discrete Frequency distribution
  • Standard Deviation for Continuous Frequency distribution

Standard Deviation Formulas:

1. Population Standard Deviation

2. Sample Standard Deviation