Question

distribution shapes
determine the shape of each distribution shown below.
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Explanation:

To determine the shape of each distribution, we analyze the skewness or uniformity:

First Distribution (Left - skewed? No, right - skewed? Wait, first graph: tail on the right)

• A distribution with a longer tail on the right is right - skewed (positively skewed). The peak is on the left, and the data tapers off to the right.

Second Distribution (Tail on the left)

• A distribution with a longer tail on the left is left - skewed (negatively skewed). The peak is on the right, and the data tapers off to the left.

Third Distribution (Flat, uniform height)

• A distribution where all values (or intervals) have approximately the same frequency is uniform (rectangular). The graph is a horizontal line (or rectangle - like), indicating equal probability/density across the range.

Fourth Distribution (Symmetric, peak in the middle, tails equal on both sides)

• A distribution that is symmetric around the mean (peak in the middle, equal tails on left and right) is symmetric (often bell - shaped, like normal distribution).

Answer:

s (assuming standard distribution shape options: Right - Skewed, Left - Skewed, Uniform, Symmetric):

1. Right - Skewed
2. Left - Skewed
3. Uniform
4. Symmetric

(Note: If the fourth graph is a perfect bell - curve, it can also be called "Normal" or "Bell - Shaped", but "Symmetric" is a broader term for such a shape.)