To determine which variable, $X$ or $Y$, exhibits more variability, we can compare the variance or standard deviation of each dataset. Variance and standard deviation are measures of how spread out the values are around the mean.

Let me first compute the mean and standard deviation for both $X$ and $Y$, and then compare their variability.

The values you provided are:

• $X = \{1.72, 0.96, 0.20\}$
• $Y = \{0.60, 1.48, 2.36\}$

I'll calculate the standard deviation (which is the square root of the variance) for both datasets.For the given dataFor the given

• The mean of $X$ is $0.96$, and its standard deviation is $0.76$.
• The mean of $Y$ is $1.48$, and its standard deviation is $0.88$.

Since the standard deviation of $Y$ (0.88) is higher than that of $X$ (0.76), we can conclude that $Y$ shows more variability compared to $X$.

If you have any further questions or want more details, feel free to ask!

Here are 5 related questions you might find helpful:

1. How is standard deviation calculated?
2. What is the difference between variance and standard deviation?
3. Why do we use the sample standard deviation (ddof=1) in statistics?
4. How does mean affect the comparison of datasets' variability?
5. What other measures can be used to compare the spread of data?

Tip: Standard deviation provides a sense of how spread out your data is. The larger the value, the more dispersed the data points are around the mean.