Question:

The mean and variance of the marks obtained by the students in a test are 10 and 4 respectively Later, the marks of one of the students is increased from 8 to 12 If the new mean of the marks is $10.2$, then their new variance is equal to :

Updated On: Mar 20, 2025
  • $3.92$
  • $3.96$
  • $4.04$
  • $4.08$
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The Correct Option is B

Solution and Explanation

1. Let the total number of students be \(n\). The initial mean is given as: \[ \text{Mean} = 10 \implies \frac{\text{Sum of marks}}{n} = 10. \] Thus, the sum of marks is: \[ \text{Sum of marks} = 10n. \] 2. After increasing one student’s marks from \(8\) to \(12\), the sum of marks becomes: \[ 10n - 8 + 12 = 10n + 4. \] 3. The new mean is given as \(10.2\): \[ \frac{10n + 4}{n} = 10.2. \] Simplify to find \(n\): \[ 10n + 4 = 10.2n \implies 0.2n = 4 \implies n = 20. \] 4. The variance formula is: \[ \text{Variance} = \frac{\sum x_i^2}{n} - (\text{Mean})^2. \] 5. Initially, the variance is \(4\): \[ \frac{\sum x_i^2}{20} - 10^2 = 4 \implies \frac{\sum x_i^2}{20} = 104 \implies \sum x_i^2 = 2080. \] 6. After the change, the updated \(\sum x_i^2\) is: \[ \sum x_i^2 = 2080 - 8^2 + 12^2 = 2080 - 64 + 144 = 2160. \] 7. The new variance is: \[ \text{New Variance} = \frac{\sum x_i^2}{20} - (\text{New Mean})^2 = \frac{2160}{20} - 10.2^2. \] Simplify: \[ \text{New Variance} = 108 - 104.04 = 3.96. \] Thus, the new variance is \(3.96\). The variance changes when marks are adjusted because it depends on both the sum of squares of individual data points and the square of the mean. Adjust both terms carefully to compute the new variance.
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Concepts Used:

Statistics

Statistics is a field of mathematics concerned with the study of data collection, data analysis, data interpretation, data presentation, and data organization. Statistics is mainly used to acquire a better understanding of data and to focus on specific applications. Also, Statistics is the process of gathering, assessing, and summarising data in a mathematical form.

Mathematically there are two approaches for analyzing data in statistics that are widely used:

Descriptive Statistics -

Using measures of central tendency and measures of dispersion, the descriptive technique of statistics is utilized to describe the data collected and summarise the data and its attributes.

Inferential Statistics -

This statistical strategy is utilized to produce conclusions from data. Inferential statistics rely on statistical tests on samples to make inferences, and it does so by discovering variations between the two groups. The p-value is calculated and differentiated to the probability of chance() = 0.05. If the p-value is less than or equivalent to, the p-value is considered statistically significant.