Concept:
The statistical mean or average of a dataset is defined as the total sum of all individual observations divided by the absolute number of observations present within that set.
$$\text{Average } (\mu) = \frac{\text{Sum of all observations}}{\text{Total number of observations}} \quad \Rightarrow \quad \text{Sum} = \text{Average} \times \text{Count}$$
Step-by-step Explanation:
Method A: Traditional Cumulative Calculation
Step 1: Compute the initial aggregate score for the first group.
We are given that the sample size $n_1 = 15$ students has a mean score of $\mu_1 = 65$.
$$\text{Sum}_{15} = \text{Average}_{15} \times 15$$
$$\text{Sum}_{15} = 65 \times 15 = 975$$
Step 2: Incorporate the incoming data point to find the new total score.
A 16th student joins the dataset with a verified individual score of 97 marks. We add this value to our previous sum:
$$\text{Sum}_{16} = \text{Sum}_{15} + \text{Score}_{\text{new}}$$
$$\text{Sum}_{16} = 975 + 97 = 1072$$
Step 3: Divide the updated sum by the total count of observations.
The total count of students has increased to $n_2 = 16$. The new mean score ($\mu_2$) is:
$$\text{Average}_{16} = \frac{\text{Sum}_{16}}{16} = \frac{1072}{16}$$
Executing long division:
$$1072 \div 16 = 68$$
Thus, the new mean mark across all 16 students is 68.
Method B: Deviational Analysis (Shortcut Method)
Alternatively, we can analyze the surplus points the new student introduces relative to the existing average baseline:
$$\text{Baseline Average} = 65$$
$$\text{New Student's Score} = 97$$
$$\text{Surplus Score } (\Delta) = 97 - 65 = +32 \text{ marks}$$
This surplus of 32 marks must be distributed equally among all 16 students in the expanded group:
$$\text{Average Increase per student} = \frac{32 \text{ marks}}{16 \text{ students}} = +2 \text{ marks}$$
$$\text{New Average} = \text{Old Average} + \text{Increase} = 65 + 2 = 68$$