
To solve this, we need to focus only on female patients whose weight is 50 kg or above. From the dataset provided (patients' gender, weight, and age – assumed from earlier context):
Step 1: Identify qualified patients All four listed above meet the weight ≥ 50 kg condition.
Step 2: Add their ages 60 + 63 + 64 + 61 = 248
Step 3: Find the average Total age ÷ Number of patients = 248 ÷ 4 = 62
Hence, the approximate average age of female patients who weigh 50 kg or above is 62 years.
Final Answer: 62
The Body Mass Index (BMI) is a measure of weight relative to height. Among the given data for patients, the calculation of BMI values shows that the maximum recorded BMI is around 27.
Option Analysis:
• 20 → Too low compared to the actual maximum.
• 33 → Too high; no patient in the dataset reaches this value.
• 30 → Slightly higher, but still not the maximum from the data.
• 27 → Correct, this matches the approximate maximum BMI.
• 23 → Falls within the normal range, but not the highest.
Conclusion: Hence, the highest BMI among all patients is approximately 27.
According to the standard Body Mass Index (BMI) classification, the normal weight range lies between 18.5 and 24.9. The oldest person considered to still fall within the normal weight category would be near the lower end of the range. Hence, a BMI of around 20 is considered appropriate and normal.
A pie chart shows the distribution of students across 5 faculties in a university. If 20% are in Arts, 25% in Science, 15% in Law, 30% in Engineering, and the rest in Commerce, what is the angle (in degrees) for Commerce?
The table given below provides the details of monthly sales (in lakhs of rupees) and the value of products returned by the customers (as a percentage of sales) of an e-commerce company for three product categories for the year 2024. Net sales (in lakhs of rupees) is defined as the difference between sales (in lakhs of rupees) and the value of products returned (in lakhs of rupees).

The plots below depict and compare the average monthly incomes (in Rs. ’000) of males and females in ten cities of India in the years 2005 and 2015. The ten cities, marked A-J in the records, are of different population sizes. For a fair comparison, to adjust for inflation, incomes for both the periods are scaled to 2025 prices. Each red dot represents the average monthly income of females in a particular city in a particular year, while each blue dot represents the average monthly income of males in a particular city in a particular year. The gender gap for a city, for a particular year, is defined as the absolute value of the average monthly income of males, minus the average monthly income of females, in that year.