Determine the mean and standard deviation for the following distribution:
| Marks | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Frequency | 1 | 6 | 6 | 8 | 8 | 2 | 2 | 3 | 0 | 2 | 1 | 0 | 0 | 0 | 1 |
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Start your 14-day free trial to unlock the full solution →The mean of the given frequency distribution is calculated by summing the products of marks and frequencies and dividing by the total frequency. The standard deviation is found using the formula involving the sum of squared marks weighted by frequencies. The mean is and the standard deviation is approximately .
To determine the mean and standard deviation for a frequency distribution, we need to understand what these measures represent. The mean () is the average value of the data, taking into account how often each value appears. It's the central point around which the data balances. The standard deviation () measures the typical spread or dispersion of the data points around this mean. A small standard deviation indicates data points are clustered closely around the mean, while a large standard deviation means they are more spread out.
For a frequency distribution where represents the individual data points (marks) and represents their corresponding frequencies, the formulas are:
Mean:
Standard Deviation:
This formula is often written as , where is the total frequency.
Let's calculate these values step-by-step.
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Organize the data and calculate necessary sums.
To efficiently calculate the mean and standard deviation, we create an extended table. This table includes columns for the marks (), frequencies (), the product , the square of the marks , and the product . The sums of the , , and columns are essential for our formulas.
Marks () Frequency () 2 1 2 4 4 3 6 18 9 54 4 6 24 16 96 5 8 40 25 200 6 8 48 36 288 7 2 14 49 98 8 2 16 64 128 9 3 27 81 243 10 0 0 100 0 11 2 22 121 242 12 1 12 144 144 13 0 0 169 0 14 0 0 196 0 15 0 0 225 0 16 1 16 256 256 Total
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