For a frequency distribution mean deviation from mean in computed by `MdotDdot=(sumf)/(sumf|d|)` (b) `MdotDdot=(sumd)/(sumf)` (c) `MdotDdot=(sumfd)/(sumf)` (d) `MdotDdot=(sumf|d|)/(sumf)`

Explanation

To solve the question regarding the formula for calculating the mean deviation from the mean in a frequency distribution, we will follow these steps:

### Step-by-Step Solution:

1. **Understand the Definitions**:
- Let \( x_i \) be the values of the data points.
- Let \( f_i \) be the frequency of each data point \( x_i \).
- The mean of the distribution, denoted as \( \bar{x} \), is calculated using the formula:
\[ \bar{x} = \frac{\sum f_i x_i}{\sum f_i} \]

2. **Calculate the Deviations**:
- The deviation of each data point from the mean is given by \( d_i = x_i - \bar{x} \).
- The absolute deviation is \( |d_i| = |x_i - \bar{x}| \).

3. **Calculate the Weighted Absolute Deviations**:
- For each data point, multiply the absolute deviation by its frequency:
\[ f_i |d_i| = f_i |x_i - \bar{x}| \]

4. **Sum the Weighted Absolute Deviations**:
- The total weighted absolute deviation is given by:
\[ \sum f_i |d_i| = \sum f_i |x_i - \bar{x}| \]

5. **Calculate the Mean Deviation**:
- The mean deviation from the mean is calculated using the formula:
\[ M_d = \frac{\sum f_i |d_i|}{\sum f_i} \]
- This formula represents the mean of the absolute deviations weighted by their frequencies.

6. **Identify the Correct Option**:
- From the options provided, we can see that:
- (d) \( M_d = \frac{\sum f_i |d|}{\sum f_i} \)
- This matches our derived formula for mean deviation.

### Conclusion:
The correct formula for the mean deviation from the mean in a frequency distribution is:
\[ M_d = \frac{\sum f_i |d|}{\sum f_i} \]
Thus, the answer is option (d).