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Let's analyze the problem based on the box-and-whisker plot and the related questions:

### a) Shape of the dataLet's analyze the problem based on the box-and-whisker plot and the related questions:

### a) Shape of the 
The box-and-whisker plot displays the number of guests at a restaurant. The right whisker (upper range) is much longer than the left whisker, suggesting that the data has a longer tail on the right side.

- **Answer**: The data is **skewed right**.

### b) Measure of center:
Since the data is skewed, the **median** is generally a better measure of central tendency than the mean, as it is less affected by extreme values in a skewed distribution.

- **Answer**: **Median** is the better measure of center.

### c) Measure of variability/spread:
For skewed data, **Interquartile Range (IQR)** is typically preferred because it is based on quartiles and is resistant to extreme values, unlike standard deviation, which can be influenced by outliers.

- **Answer**: **IQR** is the better measure of variability/spread.

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Would you like more detailed explanations on any part of this? Here are 5 related questions to deepen your understanding:

1. What does the length of the whiskers in a box plot indicate?
2. How would the box plot look for a perfectly symmetric distribution?
3. Why is the median preferred over the mean in skewed distributions?
4. What is the formula for calculating the IQR from a box plot?
5. How does skewness affect the interpretation of standard deviation?

**Tip**: In box plots, the length of the box (which represents the IQR) shows the spread of the middle 50% of the data.

The box-and-whisker plot below represents the number of guests at a local restaurant per day throughout the year.

Analyze a box-and-whisker plot representing the number of guests at a local restaurant per day. Learn how to determine skewness, the better measure of center (mean or median), and the better measure of variability (IQR or standard deviation) based on the distribution.

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