The sum of mean and variance of a given set is 15/2 and their number of trials is 10, then find the value of variance?
1. Simplify the Integrand:
We are given the equation:
\[
\mu + \sigma^2 = \frac{15}{2}
\]
where \( \mu \) is the mean and \( \sigma^2 \) is the variance.
2. Apply the Relationship Between Variance and Mean:
The relationship \( \sigma^2 = \frac{\mu}{n} \) is given. Substituting this into the sum equation:
\[
\mu + \frac{\mu}{n} = \frac{15}{2}
\]
3. Solve for \( \mu \):
Multiply through by \( n \), factor out \( \mu \), and solve:
\[
\mu = \frac{\frac{15}{2} \cdot n}{n + 1}
\]
Substituting \( n = 10 \):
\[
\mu = \frac{75}{11}
\]
4. Calculate \( \sigma^2 \):
Substitute \( \mu = \frac{75}{11} \) into \( \sigma^2 = \frac{\mu}{n} \):
\[
\sigma^2 = \frac{75}{110} = \frac{15}{22}
\]
Final Answer:
Therefore, the variance is:
\[
\sigma^2 = \frac{15}{22}
\]
Variance of the following discrete frequency distribution is:
\[ \begin{array}{|c|c|c|c|c|c|} \hline \text{Class Interval} & 0-2 & 2-4 & 4-6 & 6-8 & 8-10 \\ \hline \text{Frequency (}f_i\text{)} & 2 & 3 & 5 & 3 & 2 \\ \hline \end{array} \]
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’.
Read More: Difference Between Variance and 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’.
1. Population Standard Deviation
2. Sample Standard Deviation