To answer this question, we will follow these steps:

1. Construct the Histogram:

• The histogram is based on the weight ranges (classes) and the corresponding frequencies.

Weight (g) Range	Frequency
6.000-6.049	3
6.050-6.099	4
6.100-6.149	7
6.150-6.199	12
6.200-6.249	11
6.250-6.299	6
6.300-6.349	4
6.350-6.399	1

We can now visualize this in a histogram. Since I cannot plot directly here, let me describe how it would look:

• X-axis: This will show the weight ranges (6.000-6.049, 6.050-6.099, etc.).
• Y-axis: This will show the frequency (number of occurrences in each range).
• The bars would rise to heights based on the frequency of each weight class.

2. Does the histogram depict data that have a normal distribution?

A normal distribution generally exhibits a bell-shaped curve, where:

• Most of the data falls around the central value.
• The frequencies taper off symmetrically towards the lower and upper ends.

Based on the frequencies:

• The highest frequency (12) occurs in the 6.150-6.199 range, which is near the center.
• Frequencies decrease as we move towards the lower (6.000-6.049) and upper (6.350-6.399) classes.

The distribution appears roughly symmetric around the center, showing some characteristics of a normal distribution but not perfectly so. There is a slight skew towards the higher weights (the right-hand side frequencies taper off slower than the left).

Conclusion:

The histogram somewhat resembles a normal distribution, but the slight skew on the right-hand side suggests that it may not perfectly follow the characteristics of a normal distribution. It’s not perfectly bell-shaped and symmetric.

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Would you like to see a detailed explanation of normal distributions or a step-by-step guide on constructing histograms?

Here are 5 related questions you might find interesting:

1. What are the conditions for a perfectly normal distribution?
2. How do we measure skewness in a distribution?
3. How can we check for normality using statistical tests?
4. What other types of distributions could fit this data?
5. How does the sample size affect the appearance of a histogram?

Tip: When analyzing a histogram, observe the symmetry and the spread of the data to determine its distribution type.