To determine if the given frequency distribution has a Normal distribution, we need to assess whether the data fits the characteristics of a normal distribution. A normal distribution typically has the following features:

1. Symmetry: The distribution should be roughly symmetric around the mean.
2. Unimodal: There should be a single peak in the distribution.
3. Bell-shaped curve: The frequencies should gradually decrease as we move away from the central value.

Let's examine the dataTo determine if the given frequency distribution has a Normal distribution, we need to assess whether the data fits the characteristics of a normal distribution. A normal distribution typically has the following features:

1. Symmetry: The distribution should be roughly symmetric around the mean.
2. Unimodal: There should be a single peak in the distribution.
3. Bell-shaped curve: The frequencies should gradually decrease as we move away from the central value.

Let's examine the

Ages	Number of students
15-18	12
19-22	11
23-26	14
27-30	13
31-34	14
35-38	17

Analysis:

1. Symmetry:

   • The distribution is not perfectly symmetric, but it shows some symmetry around the central age groups (23-26, 27-30, 31-34).

2. Unimodal:

   • The distribution has a peak in the age group 35-38 (17 students), and it gradually increases towards this peak from both sides.

3. Bell-shaped curve:

   • The frequency distribution shows a bell-shaped curve but not a perfect one. The peak occurs at the older age group (35-38), which might suggest a slight skewness to the right.

Conclusion:

While the distribution does exhibit some characteristics of a normal distribution, such as a roughly bell-shaped curve and unimodality, it is not perfectly symmetric and appears slightly skewed to the right. Therefore, it is approximately normal but not perfectly normal.

So, the correct option is Approximately Normal.

Would you like more details on this analysis or have any other questions?

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Here are five related questions for further exploration:

1. How can we quantify the skewness of this distribution?
2. What methods are used to test the normality of a distribution statistically?
3. How does the mean and median help in identifying skewness in a distribution?
4. What are the implications of a distribution being approximately normal in statistical analysis?
5. How would a histogram of this data look, and how could it help in identifying normality?

Tip: When analyzing distributions, always check for symmetry, unimodality, and whether the data forms a bell-shaped curve to assess normality visually.