**Given Data:**

vad (Score): 10 – 20 10 – 30 10 – 40 10 – 50 10 – 60 10 – 70 10 – 80

vko`fRr (Freq.): 15 25 37 58 69 80 100

**Calculating the Mean:**

The mean is the average value of a set of numbers. To calculate the mean, we need to multiply each score by its corresponding frequency, sum up these products, and then divide by the total frequency.

Let's calculate the mean using the given data:

Sum of (Score x Frequency):

(10 x 15) + (20 x 25) + (30 x 37) + (40 x 58) + (50 x 69) + (60 x 80) + (70 x 100) = 150 + 500 + 1110 + 2320 + 3450 + 4800 + 7000 = 19630

Total Frequency: 15 + 25 + 37 + 58 + 69 + 80 + 100 = 384

Mean = Sum of (Score x Frequency) / Total Frequency = 19630 / 384 = 51.1354 (approx.)

So, the mean of the given data is approximately 51.1354.

**Calculating the Mean Deviation:**

The mean deviation (also known as the average deviation) measures the dispersion of data points around the mean. To calculate the mean deviation, we need to find the absolute difference between each score and the mean, multiply it by the frequency, sum up these products, and then divide by the total frequency.

Let's calculate the mean deviation using the given data:

Step 1: Find the absolute difference between each score and the mean:

Score 10: |10 - 51.1354| = 41.1354
Score 20: |20 - 51.1354| = 31.1354
Score 30: |30 - 51.1354| = 21.1354
Score 40: |40 - 51.1354| = 11.1354
Score 50: |50 - 51.1354| = 1.1354
Score 60: |60 - 51.1354| = 8.8646
Score 70: |70 - 51.1354| = 18.8646
Score 80: |80 - 51.1354| = 28.8646

Step 2: Multiply the absolute differences by their respective frequencies:

(41.1354 x 15) + (31.1354 x 25) + (21.1354 x 37) + (11.1354 x 58) + (1.1354 x 69) + (8.8646 x 80) + (18.8646 x 100) = 617.0305 + 778.386 + 781.0368 + 645.6082 + 78.4066 + 709.168 + 1886.46 = 5396.0951

Step 3: Calculate the mean deviation:

Mean Deviation = Sum of (Absolute Difference x Frequency) / Total Frequency = 5396.